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Political Participation and the Media Technical Appendix 9/14/2016 BBC Media Action Andrea Scavo
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Contents
Contents ................................................................................................................................................... 2
List of Tables ............................................................................................................................................. 3
List of Figures ............................................................................................................................................ 5
1 The sample ........................................................................................................................................ 6
2 Building the construct variables ........................................................................................................... 7
2.1 Factor analysis of construct variables........................................................................................... 8 2.1.1 Participation ...................................................................................................................... 8 2.1.2 Knowledge ...................................................................................................................... 10 2.1.3 Discussion ....................................................................................................................... 13 2.1.4 Efficacy ............................................................................................................................ 14
3 Bivariate analysis .............................................................................................................................. 17
3.1 Exposure – outcome variables .................................................................................................. 17 3.1.1 Exposure variable ............................................................................................................ 17 3.1.2 Outcome variables ........................................................................................................... 18 3.1.3 Results ............................................................................................................................ 19
3.2 Outcome variables’ correlation ................................................................................................. 20
3.3 Exposure – confounders........................................................................................................... 21 3.3.1 Description of confounders .............................................................................................. 21 3.3.2 Exposure and categorical variables .................................................................................... 24 3.3.3 Exposure and ordinal variables .......................................................................................... 27
3.4 Outcome variables – confounders ............................................................................................. 27 3.4.1 Participation .................................................................................................................... 27 3.4.2 Knowledge ...................................................................................................................... 30 3.4.3 Discussion ....................................................................................................................... 33 3.4.4 Efficacy ............................................................................................................................ 36
4 Multivariate regression analysis ......................................................................................................... 40
4.1 Regression models – Participation ............................................................................................. 42 4.1.1 Model n. 1 – Exposure with all confounders ...................................................................... 42 4.1.2 Model n. 2 – Exposure & Gender interaction ..................................................................... 44 4.1.3 Model n. 3 – Exposure & significant interactions ................................................................ 47 4.1.4 Model n. 4 – Exposure & Country interactions .................................................................. 50
4.2 Regression models – Knowledge ............................................................................................... 54 4.2.1 Model n. 1 – Exposure with all confounders ...................................................................... 54 4.2.2 Model n. 2 – Exposure & Gender interaction ..................................................................... 56 4.2.3 Model n. 3 – Exposure & significant interactions ................................................................ 59 4.2.4 Model n. 4 – Exposure & Country interactions .................................................................. 62
4.3 Regression models – Discussion ............................................................................................... 66 4.3.1 Model n. 1 – Exposure with all confounders ...................................................................... 66 4.3.2 Model n. 2 – Exposure & Gender interaction ..................................................................... 68 4.3.3 Model n. 3 – Exposure & significant interactions ................................................................ 71 4.3.4 Model n. 4 – Exposure & Country interactions .................................................................. 74
4.4 Regression models – Efficacy .................................................................................................... 78 4.4.1 Model n. 1 – Exposure with all confounders ...................................................................... 78 4.4.2 Model n. 2 – Exposure & Gender interaction ..................................................................... 80 4.4.3 Model n. 3 – Exposure & significant interactions ................................................................ 83 4.4.4 Model n. 4 – Exposure & Country interactions .................................................................. 86
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List of Tables Table 1: Data collection and Sample size by country ............................................................................................................ 6
Table 2 - Construct variables and original items .................................................................................................................... 7
Table 3 - Reliability test and Factor Analysis, Participation ................................................................................................. 9
Table 4 - Descriptives of Participation ...................................................................................................................................... 9
Table 5 - Reliability test and Factor Analysis, Knowledge (Bangladesh) ......................................................................... 10
Table 6 - Reliability test and Factor Analysis, Knowledge (Nepal)................................................................................... 11
Table 7 - Reliability test and Factor Analysis, Knowledge (Kenya) .................................................................................. 11
Table 8 - Reliability test and Factor Analysis, Knowledge (Nigeria) ................................................................................ 11
Table 9 - Reliability test and Factor Analysis, Knowledge (Tanzania) ............................................................................. 12
Table 10 - Reliability test and Factor Analysis, Knowledge (Sierra Leone).................................................................... 12
Table 11 - Reliability test and Factor Analysis, Knowledge (Myanmar) .......................................................................... 12
Table 12 - Descriptives of Knowledge .................................................................................................................................... 13
Table 13 - Reliability test and Factor Analysis, Discussion ................................................................................................. 14
Table 14 - Descriptives of Discussion ..................................................................................................................................... 14
Table 15 - Reliability test and Factor Analysis, Efficacy ....................................................................................................... 15
Table 16 - Descriptives of Efficacy ............................................................................................................................................ 15
Table 17 - List of BBC Media Action Governance debate/magazine programmes by country ................................ 18
Table 18 - Distribution of frequencies, Exposure................................................................................................................. 18
Table 19 - T-test results, Exposure - Participation .............................................................................................................. 19
Table 20 - T-test results, Exposure - Knowledge ................................................................................................................. 19
Table 21 - T-test results, Exposure - Discussion .................................................................................................................. 20
Table 22 - T-test results, Exposure - Efficacy ........................................................................................................................ 20
Table 23 - Outcomes' correlation matrix............................................................................................................................... 21
Table 24 - Distribution of frequencies, Gender .................................................................................................................... 21
Table 25 - Distribution of frequencies, Age ........................................................................................................................... 22
Table 26 - Distribution of frequencies, Location .................................................................................................................. 22
Table 27 - Distribution of frequencies, Education ................................................................................................................ 22
Table 28 - Distribution of frequencies, Income .................................................................................................................... 23
Table 29 - Distribution of frequencies, Marital status ......................................................................................................... 23
Table 30 - Distribution of frequencies, Interest .................................................................................................................... 24
Table 31 - Distribution of frequencies, Group activity ....................................................................................................... 24
Table 32 - Cross-tabulation and Chi-Square test, Exposure by Gender ........................................................................ 24
Table 33 - Cross-tabulation and Chi-Square test, Exposure by Location ...................................................................... 25
Table 34 - Cross-tabulation and Chi-Square test, Exposure by Group activity ........................................................... 25
Table 35 - Cross-tabulation and Chi-Square test, Exposure by Country ...................................................................... 26
Table 36 - Cross-tabulation and Chi-Square test, Exposure by Marital status ............................................................. 26
Table 37 - Significance testing for Exposure and ordinal variables ................................................................................... 27
Table 38 - T-test results, Gender - Participation.................................................................................................................. 27
Table 39 - T-test results, Location - Participation ................................................................................................................ 28
Table 40 - T-test results, Group activity - Participation ..................................................................................................... 28
Table 41 - ANOVA for Participation, by Country ............................................................................................................... 29
Table 42 - ANOVA for Participation, by Marital Status ..................................................................................................... 29
Table 43 - Correlation coefficients for Participation and ordinal variables ................................................................... 30
Table 44 - T-test results, Gender - Knowledge .................................................................................................................... 30
Table 45 - T-test results, Location - Knowledge .................................................................................................................. 31
Table 46 - T-test results, Group activity - Knowledge ....................................................................................................... 31
Table 47 - ANOVA for Knowledge, by Country .................................................................................................................. 32
Table 48 - ANOVA for Knowledge, by Marital Status ........................................................................................................ 32
Table 49 - Correlation coefficients for Knowledge and ordinal variables ...................................................................... 33
Table 50 - T-test results, Gender - Discussion ..................................................................................................................... 33
Table 51 - T-test results, Location - Discussion ................................................................................................................... 34
Table 52 - T-test results, Group activity - Discussion ........................................................................................................ 34
Table 53 - ANOVA for Discussion, by Country................................................................................................................... 35
Table 54 - ANOVA for Discussion, by Marital Status ......................................................................................................... 35
Table 55 - Correlation coefficients for Discussion and ordinal variables....................................................................... 36
Table 56 - T-test results, Gender - Efficacy ........................................................................................................................... 36
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Table 57 - T-test results, Location - Efficacy ......................................................................................................................... 37
Table 58 - T-test results, Group activity - Efficacy ............................................................................................................... 37
Table 59 - ANOVA for Efficacy, by Country ......................................................................................................................... 38
Table 60 - ANOVA for Efficacy, by Marital Status ............................................................................................................... 38
Table 61 - Correlation coefficients for Efficacy and ordinal variables ............................................................................. 39
Table 62 - List of regression models ........................................................................................................................................ 41
Table 63 - Model n. 1 summary - Participation ..................................................................................................................... 42
Table 64 – Model n. 1 ANOVA - Participation ..................................................................................................................... 42
Table 65 - Model n. 1 regression coefficients - Participation ............................................................................................ 43
Table 66 - Model n. 1 diagnostics - Participation .................................................................................................................. 43
Table 67 - Model n. 2 summary - Participation ..................................................................................................................... 44
Table 68 - Model n. 2 ANOVA - Participation ...................................................................................................................... 45
Table 69 - Model n. 2 regression coefficients - Participation ............................................................................................ 46
Table 70 - Model n. 2 diagnostics - Participation .................................................................................................................. 46
Table 71 - Model n. 3 summary - Participation ..................................................................................................................... 47
Table 72 - Model n. 3 ANOVA - Participation ...................................................................................................................... 48
Table 73 - Model n. 3 regression coefficients - Participation ............................................................................................ 49
Table 74 - Model n. 3 diagnostics - Participation .................................................................................................................. 50
Table 75 - Model n. 4 summary - Participation ..................................................................................................................... 50
Table 76 - Model n. 4 ANOVA - Participation ...................................................................................................................... 51
Table 77 - Model n. 4 regression coefficients - Participation ............................................................................................ 52
Table 78 - Model n. 4 diagnostics - Participation .................................................................................................................. 52
Table 79 - Model n. 1 summary - Knowledge ....................................................................................................................... 54
Table 80 - Model n. 1 ANOVA - Knowledge ........................................................................................................................ 54
Table 81 - Model n. 1 regression coefficients - Knowledge ............................................................................................... 55
Table 82 - Model n. 1 diagnostics - Knowledge .................................................................................................................... 55
Table 83 - Model n. 2 summary - Knowledge ....................................................................................................................... 56
Table 84 - Model n. 2 ANOVA - Knowledge ........................................................................................................................ 57
Table 85 - Model n. 2 regression coefficients - Knowledge ............................................................................................... 58
Table 86 - Model n. 2 diagnostics - Knowledge .................................................................................................................... 58
Table 87 - Model n. 3 summary - Knowledge ....................................................................................................................... 59
Table 88 - Model n. 3 ANOVA - Knowledge ........................................................................................................................ 60
Table 89 - Model n. 3 regression coefficients - Knowledge ............................................................................................... 61
Table 90 - Model n. 3 diagnostics - Knowledge .................................................................................................................... 61
Table 91 - Model n. 4 summary - Knowledge ....................................................................................................................... 62
Table 92 - Model n. 4 ANOVA - Knowledge ........................................................................................................................ 63
Table 93 - Model n. 4 regression coefficients - Knowledge ............................................................................................... 64
Table 94 - Model n. 4 diagnostics - Knowledge .................................................................................................................... 64
Table 95 - Model n. 1 summary - Discussion ........................................................................................................................ 66
Table 96 - Model n. 1 ANOVA - Discussion ......................................................................................................................... 66
Table 97 - Model n. 1 regression coefficients - Discussion ................................................................................................ 67
Table 98 - Model n. 1 diagnostics - Discussion ..................................................................................................................... 67
Table 99 - Model n. 2 summary - Discussion ........................................................................................................................ 68
Table 100 - Model n. 2 ANOVA - Discussion ....................................................................................................................... 69
Table 101 - Model n. 2 regression coefficients - Discussion ............................................................................................. 70
Table 102 - Model n. 2 diagnostics - Discussion ................................................................................................................... 70
Table 103 - Model n. 3 summary - Discussion ...................................................................................................................... 71
Table 104 - Model n. 3 ANOVA - Discussion ....................................................................................................................... 72
Table 105 - Model n. 3 regression coefficients - Discussion ............................................................................................. 73
Table 106 - Model n. 3 diagnostics - Discussion ................................................................................................................... 73
Table 107 - Model n. 4 summary - Discussion ...................................................................................................................... 74
Table 108 - Model n. 4 ANOVA - Discussion ....................................................................................................................... 75
Table 109 - Model n. 4 regression coefficients - Discussion ............................................................................................. 76
Table 110 - Model n. 4 diagnostics - Discussion ................................................................................................................... 76
Table 111 - Model n. 1 summary - Efficacy ............................................................................................................................ 78
Table 112 - Model n. 1 ANOVA - Efficacy ............................................................................................................................. 78
Table 113 - Model n. 1 regression coefficients - Efficacy .................................................................................................... 79
Table 114 - Model n. 1 diagnostics - Efficacy ......................................................................................................................... 79
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Table 115 - Model n. 2 summary - Efficacy ............................................................................................................................ 80
Table 116 - Model n. 2 ANOVA - Efficacy ............................................................................................................................. 81
Table 117 - Model n. 2 regression coefficients - Efficacy .................................................................................................... 82
Table 118 - Model n. 2 diagnostics - Efficacy ......................................................................................................................... 82
Table 119 - Model n. 3 summary - Efficacy ............................................................................................................................ 83
Table 120 - Model n. 3 ANOVA - Efficacy ............................................................................................................................. 84
Table 121 - Model n. 3 regression coefficients - Efficacy .................................................................................................... 85
Table 122 - Model n. 3 diagnostics - Efficacy ......................................................................................................................... 85
Table 123 - Model n. 4 summary - Efficacy ............................................................................................................................ 86
Table 124 - Model n. 4 ANOVA - Efficacy ............................................................................................................................. 87
Table 125 - Model n. 4 regression coefficients - Efficacy .................................................................................................... 88
Table 126 - Model n. 4 diagnostics - Efficacy ......................................................................................................................... 88
List of Figures Figure 1 - Distribution of frequencies, Participation ............................................................................................................ 10
Figure 2 - Normal Q-Q plot, Participation............................................................................................................................. 10
Figure 3 - Distribution of frequencies, Knowledge .............................................................................................................. 13
Figure 4 - Normal Q-Q plot, Knowledge ............................................................................................................................... 13
Figure 5 - Distribution of values, Discussion ......................................................................................................................... 14
Figure 6 - Normal Q-Q plot, Discussion ................................................................................................................................ 14
Figure 7 - Distribution of frequencies, Efficacy ...................................................................................................................... 16
Figure 8 - Normal Q-Q plot, Efficacy ...................................................................................................................................... 16
Figure 9 - Residuals and predicted values - Model n. 1 - Participation ........................................................................... 44
Figure 10 - Residuals and predicted values - Model n. 2 - Participation ......................................................................... 47
Figure 11 - Residuals and predicted values - Model n. 3 - Participation ......................................................................... 50
Figure 12 - Residuals and predicted values - Model n. 4 - Participation ......................................................................... 53
Figure 13 - Residuals and predicted values - Model n. 1 - Knowledge............................................................................ 56
Figure 14 - Residuals and predicted values - Model n. 2 - Knowledge............................................................................ 59
Figure 15 - Residuals and predicted values - Model n. 3 - Knowledge............................................................................ 62
Figure 16 - Residuals and predicted values - Model n. 4 - Knowledge............................................................................ 65
Figure 17 - Residuals and predicted values - Model n. 1 - Discussion............................................................................. 68
Figure 18 - Residuals and predicted values - Model n. 2 - Discussion............................................................................. 71
Figure 19 - Residuals and predicted values - Model n. 3 - Discussion............................................................................. 74
Figure 20 - Residuals and predicted values - Model n. 4 - Discussion............................................................................. 77
Figure 21 - Residuals and predicted values - Model n. 1 - Efficacy ................................................................................... 80
Figure 22 - Residuals and predicted values - Model n. 2 - Efficacy ................................................................................... 83
Figure 23 - Residuals and predicted values - Model n. 3 - Efficacy ................................................................................... 86
Figure 24 - Residuals and predicted values - Model n. 4 - Efficacy ................................................................................... 89
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TECHNICAL APPENDIX
This appendix details the processes used to construct the models that have produced the results
presented in the main report. First, data used in the analysis are discussed, describing how they were
collected and modelled for the analysis. Second, the process of deriving the construct variables (i.e.
Participation, Knowledge, Discussion, and Efficacy) through Exploratory Factor Analysis is detailed.
Third, the bivariate analysis methods employed for the analysis of the relationships between
exposure to BBC Governance programming and those construct variables are presented and
discussed. Finally, the regression models for the multivariate analysis of the same relationships, while
controlling for socio-political and demographic confounders, are discussed.
1 The sample
This research is based on multi-country, cross-national data. All data were collected through primary
research carried out by BBC Media Action. All the analyses were conducted on a single dataset of
23621 cases, collected across seven countries at various points in time: Bangladesh, Nepal, Kenya,
Nigeria, Tanzania, Sierra Leone, and Myanmar. Where multiple phases of data collection were
carried out, only the most recent single dataset from each country was incorporated into the
composite dataset.
Table 1: Data collection and Sample size by country
Country Data Collection Sample size
Bangladesh July 2015 2650
Myanmar August 2013 1224
Nepal January 2016 4000
Kenya January 2015 3003
Nigeria December 2014 4240
Sierra Leone July 2013 4389
Tanzania August 2013 4114
Data were originally collected for analysis at national level. Therefore, we needed to merge seven
different datasets and to check for consistency of the variables across countries. This is because
there were slight differences in the way questions were asked to respondents, due to cultural and
linguistic differences across countries. Some questions were asked differently from one country to
another, while others were not asked at all in some countries. Therefore, we needed to select for
the analysis only those variables that were consistently measured across countries, leaving out of the
analysis potentially relevant variables that were not measured in all countries (such as disability –
which was measured only in Bangladesh, Kenya and Nigeria – and trust in political institutions –
which was not measured in Nepal and Myanmar).
Samples are representative of national adult population (15+) in all of the seven countries. Our
sampling approach is random, self-weighting in all countries1. Samples are stratified for region (or
1 We applied Probability Proportional to Size (PPS) sampling for selection of districts, wards and villages,
ensuring that strata’s population proportions fall within 95% confidence intervals around sample’s proportions
in all cases.
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other intra-country administrative sub-divisions) and urban/rural location. For these reasons we did
not weight the data.
2 Building the construct variables
This section details the process undertaken to derive construct variables, considered as outcomes in
the analysis. We define as construct variables all those variables that we did not measure directly
in our surveys but that we derived from other variables measured directly (referred to as items).
See Table 2 for a list of the construct variables together with the items they were derived from.
Table 2 - Construct variables and original items
CONSTRUCT ITEMS LABEL ORIGINAL VALUES
PARTICIPATION
ParticipationA Participation - In an organised effort to
solve a neighbourhood or community
problem
0 – Not done
1 – Done once
2 – Done several times
ParticipationB Participation - Attended a meeting of the
local town council
ParticipationC Participation - Contacted a local official
ParticipationD Participation - Contacted a national
elected official
ParticipationE Participation - Contacted a local chief or
traditional leader about an issue
ParticipationF Participation - Taken part in a protest,
march, or demonstration
VotingA Voting - Likelihood to vote to next
general elections 0 – Very unlikely
1 – Somewhat unlikely
2 – Somewhat likely
3 – Very likely VotingB
Voting - Likelihood to vote to next local
elections
KNOWLEDGE
- depending on
country
specificities2
0 – Nothing at all
1 – Not very much
2 – A fair amount
3 – A great deal
DISCUSSION
DiscussionA Discussion - Frequency with family
members 0 – Never
1 – Occasionally
2 - Frequently
DiscussionB Discussion - Frequency with with friends
DiscussionC Discussion - Frequency with people
outside family and friends
EFFICACY
EmpowermentA Empowerment - Entitlement to question
0 – Strongly disagree
1 – Disagree
2 – Agree
3 – Strongly agree
EmpowermentB Empowerment - There are ways to
question
EmpowermentC Empowerment - Satisfied with the current
account politicians give
ExtEfficacyA ExtEfficacy - Government listens when
people get together
ExtEfficacyC ExtEfficacy - National government acts on
the need of ordinary people
We adopted the same approach for deriving each one of the construct variables. Firstly, we selected
a list of items that were:
- related to the concept the construct variable is meant to measure, according to the relevant
literature on the subject and to previous BBC Media Action’s research3;
2 Refer to specific country tables below (Tables 5 – 11).
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- available in all national datasets.
Secondly, when needed, we recoded the items in order to have a homogeneous measure across
countries. This included re-scaling items (e.g. from four-point to three-point scales), since original
measures were not homogeneous across countries.
Thirdly, we ran Exploratory Factory Analysis, aiming at checking the consistency among the original
items and their correlation with the factor(s) extracted and, therefore, refining the list of original
items for each construct. We looked at Standardised Cronbach’s Alpha, Kaiser-Meyer-Olkin
Measure of Sampling Adequacy, the proportion of items’ variance explained by the factor(s), and the
factor loadings to evaluate the goodness of the different possible factors structures. Following
convention, we considered:
- a minimum threshold of 0.5 for Standardised Cronbach’s Alpha;
- a minimum threshold of 0.6 for Kaiser-Meyer-Olkin Measure of Sampling Adequacy;
- a minimum threshold of 40% of explained variance;
- a minimum of 0.4 for each item’s factor loading4.
Where possible, we aimed at identifying one single factor through Principal Axis Factoring extraction
method (since items’ distributions were not normal in most cases).
Fourthly, we checked if the preferred factor solutions hold consistently across countries, by running
Confirmatory Factor Analysis in each national dataset with the identified solutions.
Fifthly, once we obtained a refined list of original items that load well enough into the single
construct, we computed a simple average of their scores in order to have a single measure of the
construct.
Sixthly and finally, we re-scaled the construct’s value to a 0 to 10 scale for comparability purposes.
2.1 Factor analysis of construct variables
2.1.1 Participation
Exploratory Factor Analysis of eight observed variables allows us to identify “Political Participation”
as a single latent variable, explaining more than one third of the total variance5.
Based on 20631 valid cases (87.3% of total) the Cronbach's Alpha is 0.746, which means the
consistency among items is quite high.
3 See, for example, “How do debate programmes influence knowledge of key governance issues and political
participation?” (available at www.bbc.co.uk/mediaaction/publications-and-
resources/research/briefing/africa/sierra-leone/governance) and “How do political debate programmes
influence political participation? A case study from Nepal” (available at
www.bbc.co.uk/mediaaction/publications-and-resources/research/reports/asia/nepal/research-nepal-debate-
political-participation). 4 Single exceptions to these rules of thumb will be discussed in the detailed description of each construct
below. 5 This is the only case in which the explained variance is below the 40% threshold. However, considering the
relatively high number of items (8) this is acceptable.
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Sample adequacy is tested both with a KMO Measure (that is 0.718) and a Bartlett's Test of
Sphericity, which proved to be extremely significant (<0.001).
Participation is particularly related to ParticipationB (Attended a meeting of the local town council).
In the case of ParticipationF (Taken part in a protest, march, or demonstration) the factor loading is
below the 0.4 threshold. However, this is understandable since this form of participation is often
negatively perceived, especially in less democratic countries.
Table 3 - Reliability test and Factor Analysis, Participation
CONSTRUCT ITEMS LABEL FACTOR
LOADINGS
PARTICIPATION
ParticipationA Participation - In an organised effort to solve a neighbourhood or
community problem 0.605
ParticipationB Participation - Attended a meeting of the local town council 0.695
ParticipationC Participation - Contacted a local official 0.674
ParticipationD Participation - Contacted a national elected official 0.551
ParticipationE Participation - Contacted a local chief or traditional leader about an
issue 0.597
ParticipationF Participation - Taken part in a protest, march, or demonstration 0.358
VotingA Voting - Likelihood to vote to next general elections 0.445
VotingB Voting - Likelihood to vote to next local elections 0.426
CRONBACH'S
ALPHA KMO N
BARTLETT TEST
(α=0.01) EIGENVALUE % OF VAR.
Χ2 df p-value
0.746 0.718 20631 62034.795 28 <0.001 2.997 37.5%
The distribution of frequencies for Participation is somewhat positively skewed, while it may be
considered mesokurtic. As the Normal Q-Q plot shows, the distribution is close to normality.
Table 4 - Descriptives of Participation
N Valid 23590
Missing 31
Mean 3.7157
Median 3.1250
Std. Deviation 2.08847
Skewness .740
Std. Error of Skewness .016
Kurtosis .186
Std. Error of Kurtosis .032
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2.1.2 Knowledge
As already stated in the introduction of this section, we derived this construct variable through a
partially different process. Since questions on self-reported level of knowledge necessarily needed to
be related to countries’ specific political agendas, it was not possible to ask respondents a
predetermined set of questions. Therefore, the questions actually asked vary from one country to
another. Nonetheless, data are still comparable since the rationale of the questions’ selection was
consistent across countries. Questions relate to, indeed, the topics mainly covered by BBC Media
Action Governance programming, which are in turn selected from amongst the most relevant issues
in the public and political debate in each country.
The tables below report the main results of the reliability test and the factor analysis for each
country, also specifying which topics were covered in each country’s questions on self-reported
political knowledge.
In all cases the relevant parameters are above the defined thresholds (as they are defined at page 8).
Table 5 - Reliability test and Factor Analysis, Knowledge (Bangladesh)
COUNTRY LABEL FACTOR
LOADINGS
Bangladesh
Recent violence and hartal strikes/blockades following the general election in 2014 0.814
Demand for more discussion between government and the opposition to end the
current political unrest 0.833
Leaking of questions from public exams (e.g. SSC, HSC, BCS) 0.697
Decisions of the war crime tribunal and issuing of death penalties 0.841
CRONBACH'S
ALPHA KMO N
BARTLETT TEST (α=0.01) EIGENVALUE % OF VAR.
Χ2 df p-value
0.873 0.811 2301 4742.747 6 <0.001 2.903 72.6%
Figure 1 - Distribution of frequencies, Participation Figure 2 - Normal Q-Q plot, Participation
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Table 6 - Reliability test and Factor Analysis, Knowledge (Nepal)
COUNTRY LABEL FACTOR
LOADINGS
Nepal
The new constitution 0.596
The Government’s response to the earthquake and the aftermath 0.65
Dalit issues 0.752
Gender issues 0.747
Employment 0.813
Migrant issues 0.773
Development issues 0.783
CRONBACH'S
ALPHA KMO N
BARTLETT TEST
(α=0.01) EIGENVALUE % OF VAR.
Χ2 df p-value
0.889 0.902 3561 12394.2 21 <0.001 4.218 60.3%
Table 7 - Reliability test and Factor Analysis, Knowledge (Kenya)
COUNTRY LABEL FACTOR
LOADINGS
Kenya
The new constitution 0.596
Employment 0.813
Migrant issues 0.773
Development issues 0.783
CRONBACH'S
ALPHA KMO N
BARTLETT TEST (α=0.01) EIGENVALUE % OF VAR.
Χ2 df p-value
0.768 0.777 2784 2675.439 6 <0.001 2.359 59.0%
Table 8 - Reliability test and Factor Analysis, Knowledge (Nigeria)
COUNTRY LABEL FACTOR
LOADINGS
Nigeria
Corruption in government 0.804
Ethnic related conflicts 0.759
Poor delivery of public services 0.788
The national budget 0.714
Inequality between women and men 0.69
CRONBACH'S
ALPHA KMO N
BARTLETT TEST
(α=0.01) EIGENVALUE % OF VAR.
Χ2 df p-value
0.866 0.852 4048 9114.03 10 <0.001 3.258 65.2%
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Table 9 - Reliability test and Factor Analysis, Knowledge (Tanzania)
COUNTRY LABEL FACTOR
LOADINGS
Tanzania
Maternal health 0.593
Access to clean water 0.761
Health infrastructure 0.844
Transport infrastructure 0.774
CRONBACH'S
ALPHA KMO N
BARTLETT TEST
(α=0.01) EIGENVALUE % OF VAR.
Χ2 df p-value
0.83 0.782 3992 6234.79 6 <0.001 2.658 66.5%
Table 10 - Reliability test and Factor Analysis, Knowledge (Sierra Leone)
COUNTRY LABEL FACTOR
LOADINGS
Sierra Leone
Women’s rights 0.742
Political party agendas 0.808
Water and electricity service delivery 0.675
Corruption 0.733
CRONBACH'S
ALPHA KMO N
BARTLETT TEST
(α=0.01) EIGENVALUE % OF VAR.
Χ2 df p-value
0.828 0.789 3725 5434.99 6 <0.001 2.641 66.0%
Table 11 - Reliability test and Factor Analysis, Knowledge (Myanmar)
COUNTRY LABEL FACTOR
LOADINGS
Myanmar
New foreign company investments in Myanmar 0.746
The Kachin conflict and peace negotiations 0.746
Crisis in Rakhine and Meikhtila 0.736
Efforts to reduce corrpution within government 0.706
Ethnic and religious diversity of Myanmar 0.696
Opportunities for volunteering and participating in your community 0.542
Individual economic and employment rights 0.644
CRONBACH'S
ALPHA KMO N
BARTLETT TEST
(α=0.01) EIGENVALUE % OF VAR.
Χ2 df p-value
0.863 0.871 971 2771.62 21 <0.001 3.854 55.1%
The distribution of Knowledge values is substantially symmetric, although a bit platykurtic.
Nonetheless, we may consider it close to normality, as the Normal Q-Q plot shows.
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Table 12 - Descriptives of Knowledge
N Valid 23030
Missing 591
Mean 4.7725
Median 5.0010
Std. Deviation 2.523783
Skewness -.090
Std. Error of Skewness .016
Kurtosis -.567
Std. Error of Kurtosis .032
2.1.3 Discussion
Exploratory Factor Analysis of three observed variables allows us to identify “Discussion” as a single
latent variable, explaining roughly two thirds of the total variance.
Based on no. 22871 valid cases (96.8% of total) the Cronbach's Alpha is 0.758, which means the
consistency among items is quite high.
Sample adequacy is tested both with a KMO Measure (that is 0.676) and a Bartlett's Test of
Sphericity, which proved to be extremely significant (<0.001).
Discussion is particularly related to DiscussionB (Frequency with friends).
Figure 3 - Distribution of frequencies, Knowledge Figure 4 - Normal Q-Q plot, Knowledge
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Table 13 - Reliability test and Factor Analysis, Discussion
CONSTRUCT ITEMS LABEL FACTOR
LOADINGS
DISCUSSION
DiscussionA Discussion - Frequency with family members 0.661
DiscussionB Discussion - Frequency with friends 0.837
DiscussionC Discussion - Frequency with people outside family and friends 0.652
CRONBACH'S
ALPHA KMO N
BARTLETT TEST
(α=0.01) EIGENVALUE % OF VAR.
Χ2 df p-value
0.758 0.676 22871 17269.314 3 <0.001 2.022 67.4%
The distribution of Discussion is practically symmetric, while it is somewhat platykurtic. However,
also in this case the Normal Q-Q plot, we can consider this distribution close to normality.
Table 14 - Descriptives of Discussion
N Valid 23398
Missing 223
Mean 4.5404
Median 5.0010
Std. Deviation 2.82137
Skewness .049
Std. Error of Skewness .016
Kurtosis -.705
Std. Error of Kurtosis .032
2.1.4 Efficacy
Exploratory Factor Analysis of five observed variables allows us to identify “Efficacy” as a single
latent variable, explaining roughly almost half of the total variance.
Figure 5 - Distribution of values, Discussion Figure 6 - Normal Q-Q plot, Discussion
15
Based on no. 17918 valid cases (75.9% of total) the Cronbach's Alpha is 0.635, which means the
consistency among items is not as high as in the cases of Participation, Discussion, and the
Knowledge constructs, but it is still acceptable since well above the 0.5 threshold.
Sample adequacy is tested both with a KMO Measure (0.667) and a Bartlett's Test of Sphericity,
which proved to be extremely significant (<0.001).
Efficacy is moderately related to all of the five original items, ranging from EmpowermentA
(Entitlement to question), whose loading is 0.495, and ExtEfficacyC (National government acts on
the need of ordinary people), whose loading is 0.63.
Table 15 - Reliability test and Factor Analysis, Efficacy
CONSTRUCT ITEMS LABEL FACTOR
LOADINGS
EFFICACY
EmpowermentA Empowerment - Entitlement to question 0.495
EmpowermentB Empowerment - There are ways to question 0.562
EmpowermentC Empowerment - Satisfied with the current account politicians give 0.511
ExtEfficacyA ExtEfficacy - Government listens when people get together 0.506
ExtEfficacyC ExtEfficacy - National government acts on the need of ordinary people
0.63
CRONBACH'S ALPHA
KMO N BARTLETT TEST (α=0.01)
EIGENVALUE % OF VAR. Χ
2 df p-value
0.635 0.667 17918 8120.907 6 <0.001 1.857 46.4%
Efficacy appears to be distributed normally. Both skewness and kurtosis values are relatively close to
0, and the Normal Q-Q plot shows that the distribution is close to normality.
Table 16 - Descriptives of Efficacy
N Valid 23126
Missing 495
Mean 5.4333
Median 5.3333
Std. Deviation 1.90376
Skewness -.135
Std. Error of Skewness .016
Kurtosis .244
Std. Error of Kurtosis .032
16
Figure 7 - Distribution of frequencies, Efficacy Figure 8 - Normal Q-Q plot, Efficacy
17
3 Bivariate analysis
This section describes the analysis we conducted in order to measure the strength and the direction
of bivariate relationships between pairs of variable involved in this study, as well as to test their
significance.
More precisely, we analysed:
- the relationship between our main independent variable, Exposure, and the construct
variables we defined as outcomes (Participation, Discussion, Knowledge and Efficacy);
- the relationships among outcome variables;
- the relationship between Exposure and all the socio-demographic variables potentially
associated to it (referred to as “confounders”);
- the relationship between our outcome variables and confounders.
We conducted different types of significance test, according to the nature of the variables
considered. T-tests for means difference, Mann-Whitney U-tests, Pearson’s R and Spearman’s Rho
correlation coefficients and Chi-squared significance tests were conducted to test the association of
each pair of variable. All significance tests were conducted with α = 0.01.
The following sections report the parameters and the results of the significance testing for all of the
relationships analysed.
3.1 Exposure – outcome variables
3.1.1 Exposure variable
Exposure is a binary variable, derived from a set of questions about awareness of BBC Media Action
Governance programming6, recentness of last listening to / watching the programme, and frequency
of listening/watching. Therefore, we defined:
- Non-reached people as those who have not listened to / watched any BBC Media Action
governance programme during the last 12 months;
- Reached people as those who are aware of at least one BBC Media Action governance
programme and have listened to / watched it during the last 12 months;
- Regularly reached people as those who are aware of at least one BBC Media Action
governance programme and have listened to / watched it during the last 12 months, and
have listened to / watched every other episode (at least);
- Media dark people as those who have not accessed any relevant media during the last 12
months.
6 In this research we specifically considered only BBC Media Action programmes that have a talk or debate
format. For a list of the actual programmes, see Table 17.
18
Table 17 - List of BBC Media Action Governance debate/magazine programmes by country
Country Programme Format Platform Since
Bangladesh Sanglap Debate TV/Radio
2005 (3rd series started
2012)
Myanmar Lin Lait Kyair Sin Magazine Radio 2011
Current Affairs Debate TV 2014
Lively News Magazine Radio
Kenya Sema Kenya Debate TV 2012
Nepal Sajha Sawal Debate TV 2007
Nigeria GGK Magazine Radio 2013 (after 2 years off air)
Sierra Leone Fo Rod Magazine Radio 2011
Tok Bot Salone Debate Radio 2012
Tanzania Haba Na Haba Magazine Radio
In our analysis, we set ‘reached (but not regularly)’ and ‘media dark’ respondents as missing cases,
since we want to detect the ‘effect’ of full exposure to the programmes on our potential audience.
Therefore, the Exposure variable assumes a “0” value for not reached respondents and “1” for those
who are regularly reached by at least one programme (in case there is more than one programme
broadcasted in their country, as in the case of Myanmar or Sierra Leone).
Table 18 - Distribution of frequencies, Exposure
Exposure to at least one governance programme
Frequency Percent Valid Percent Cumulative Percent
Valid
Not reached 15875 67.2 80.8 80.8
Regularly reached 3778 16.0 19.2 100.0
Total 19653 83.2 100.0
Missing
Reached (but not regularly) 1176 5.0 Media dark 2792 11.8 Total 3968 16.8
Total 23621 100.0
3.1.2 Outcome variables
As described in Section 2 of this Technical Appendix, we derived all of the outcome variables
constructs from several original items. For each construct, we re-scaled the average score of the
original items into a 0-10 scale in order to have comparable measures of our dependent variables.
See Tables 4, 6, 14, and 16, and Figures 1-4 for each variable’s main descriptive parameters and
distributions of frequencies.
19
3.1.3 Results
Exposure is significantly and positively associated with all of the outcome variables except Efficacy.
Exposed people report higher Participation (+0.99), Discussion (+1.24), and Knowledge (+1.34)
scores. The difference between exposed and unexposed people in Efficacy scores is very little (0.05)
and not significant.
In all cases the assumption of equal variances in the two groups is not met according to the Levene’s
test. Therefore, we conducted a Welch’s t-test to test the significance of mean differences.
Due to the large size of the sample, the significance level has been set at 0.01.
Table 19 - T-test results, Exposure - Participation
Exposure to at least one
governance programme N Mean
Std.
Deviation
Std.
Error
Mean
Average
political
participation
(0 to 10)
Regularly
reached 3778 4.5323 2.23057 .03629
Not reached 15869 3.5381 2.00155 .01588
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
99% Confidence
Interval of the
Difference
Lower Upper
Equal
variances
assumed 166.297 < 0.001
26.830 19645 < 0.001 .99412 .03705 .89868 1.08957
Equal
variances not
assumed
25.096 5315.742 < 0.001 .99412 .03961 .89205 1.09620
Table 20 - T-test results, Exposure - Knowledge
Exposure to at least one
governance programme N Mean
Std.
Deviation
Std. Error
Mean
Average Self-
reported
knowledge (0
to 10)
Regularly
reached 3761 5.9344 2.24430 .03660
Not reached 15566 4.5981 2.47893 .01987
Levene's Test
for Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
99% Confidence
Interval of the
Difference
Lower Upper
Equal
variances
assumed 95.787 < 0.001
30.203 19325 < 0.001 1.33631 .04424 1.22234 1.45029
Equal
variances not
assumed
32.091 6173.842 < 0.001 1.33631 .04164 1.22902 1.44361
20
Table 21 - T-test results, Exposure - Discussion
Exposure to at least one
governance programme N Mean
Std.
Deviation
Std. Error
Mean
Average
discussion
frequency (0
to 10)
Regularly
reached 3772 5.6482 2.56913 .04183
Not reached 15783 4.4075 2.81353 .02240
Levene's Test
for Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
99% Confidence
Interval of the
Difference
Lower Upper
Equal
variances
assumed 56.431 < 0.001
24.731 19553 < 0.001 1.24071 .05017 1.11148 1.36995
Equal
variances not
assumed
26.148 6122.352 < 0.001 1.24071 .04745 1.11845 1.36297
Table 22 - T-test results, Exposure - Efficacy
Exposure to at least one
governance programme N Mean
Std.
Deviation
Std. Error
Mean
Efficacy (0 to
10)
Regularly
reached 3772 5.4748 1.78621 .02908
Not reached 15619 5.4201 1.92668 .01542
Levene's Test
for Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
99% Confidence
Interval of the
Difference
Lower Upper
Equal
variances
assumed 25.160 < 0.001
1.586 19389 .113 .05468 .03447 -.03413 0.14348
Equal
variances
not assumed
1.661 6072.102 .097 .05468 .03292 -.03014 0.13949
3.2 Outcome variables’ correlation
We tested the associations among the outcome variables, computing Pearson’s correlation
coefficients and testing for their significance. Significance tests were 1-tailed with α = 0.01.
All outcome variables are positively correlated each other. Pearson’s correlation are in all cases
significantly greater than 0 at 0.001 level. Correlations are moderate (> 0.3) in the cases of
Participation and Discussion, and of Discussion and Knowledge, while they are weak (> 0.1) for
21
Participation and Knowledge, Participation and Efficacy, and Knowledge and Efficacy. The correlation
between Discussion and Efficacy is very weak (< 0.1).
Table 23 reports coefficients and their significance.
Table 23 - Outcomes' correlation matrix
Average political
participation (0
to 10)
Average
discussion
frequency (0 to
10)
Average Self-
reported
knowledge (0 to
10)
Efficacy (0 to 10)
Average political
participation (0 to
10)
Pearson
Correlation 1 0.361 0.284 0.148
Sig. (1-tailed) < 0.001 < 0.001 < 0.001
N 23590 23388 23018 23121
Average discussion
frequency (0 to 10)
Pearson
Correlation 1 0.349 0.037
Sig. (1-tailed) < 0.001 < 0.001
N 23398 22918 22976
Average Self-
reported knowledge
(0 to 10)
Pearson
Correlation 1 0.112
Sig. (1-tailed) < 0.001
N 23030 22657
Efficacy (0 to 10)
Pearson
Correlation 1
Sig. (1-tailed)
N 23126
3.3 Exposure – confounders
We included several socio-demographic characteristics in the analysis. These have been selected as
potentially influencing factors, related to the outcome variables and/or to Exposure, which is the
hypothesised explanatory variable. Therefore, before including them in the multivariate regression
models, we tested their association with Exposure and with the outcome variables (see Par. 3.4).
3.3.1 Description of confounders
3.3.1.1 Gender
Table 24 - Distribution of frequencies, Gender
Frequency Percent Valid Percent Cumulative Percent
Valid
Male 11904 50.4 50.4 50.4
Female 11716 49.6 49.6 100.0
Total 23620 100.0 100.0
Missing System 1 .0
Total 23621 100.0
22
3.3.1.2 Age
We grouped the original Age (numeric) variable into a 6-category banded ordinal variable.
Table 25 - Distribution of frequencies, Age
Frequency Percent Valid Percent Cumulative Percent
Valid
15-24 7031 29.8 29.8 29.8
24-34 6869 29.1 29.1 58.9
35-44 4198 17.8 17.8 76.7
45-54 2720 11.5 11.5 88.2
55-64 1633 6.9 6.9 95.2
65+ 1140 4.8 4.8 100.0
Total 23591 99.9 100.0
Missing System 30 .1
Total 23621 100.0
3.3.1.3 Location
Table 26 - Distribution of frequencies, Location
Frequency Percent Valid Percent Cumulative Percent
Valid
Rural 15503 65.6 65.6 65.6
Urban 8118 34.4 34.4 100.0
Total 23621 100.0 100.0
3.3.1.4 Education level
Education is an ordinal variable derived from questions concerning both literacy and ‘formal’
education, in terms of completed levels of education. We classified everyone who stated that they
have major difficulties in reading a written text in their main language as ‘Non-literate’, regardless the
level of formal education declared.
Table 27 - Distribution of frequencies, Education
Frequency Percent Valid Percent Cumulative Percent
Valid
Non-literate 3836 16.2 16.6 16.6
Literate but not schooling 2937 12.4 12.7 29.3
Completed primary 5056 21.4 21.9 51.2
Completed secondary 7684 32.5 33.3 84.5
Completed higher education 3576 15.1 15.5 100.0
Total 23089 97.7 100.0
Missing Unknown 532 2.3
Total 23621 100.0
3.3.1.5 Income
Income is an ordinal variable that derives from a single question on the self-reported purchasing
power, for which the possible answers were:
We don’t have enough money, even for food;
We can afford food but purchasing of clothes is a serious problem;
23
We can afford food and clothes, but purchasing of durables such as a TV set or a
refrigerator is difficult for us;
We can afford main household appliances, but purchasing a car is beyond our means;
What we earn is sufficient to buy anything except such expensive purchases as an apartment
or house;
We do not face financial problems. If necessary we can buy an apartment or a house.
We considered the first two categories as ‘low’ income level, the third and the fourth as ‘medium’,
and the last two categories as ‘high’.
Table 28 - Distribution of frequencies, Income
Frequency Percent Valid Percent Cumulative Percent
Valid
Low 5652 23.9 24.9 24.9
Medium 15041 63.7 66.1 91.0
High 2047 8.7 9.0 100.0
Total 22740 96.3 100.0
Missing
DK 676 2.9 REF 205 .9 Total 881 3.7
Total 23621 100.0
3.3.1.6 Marital status
Table 29 - Distribution of frequencies, Marital status
Frequency Percent Valid Percent Cumulative Percent
Valid
Single 7304 30.9 31.3 31.3
Married, living with spouse 13132 55.6 56.3 87.7
Married, not living with spouse 1090 4.6 4.7 92.4
Divorced/separated 430 1.8 1.8 94.2
Widowed 953 4.0 4.1 98.3
In a marriage where the husband
has more than one wife 226 1.0 1.0 99.3
Living with partner 173 .7 .7 100.0
Total 23308 98.7 100.0
Missing System 313 1.3
Total 23621 100.0
3.3.1.7 Interest in politics
Interest is an ordinal variable specifying the self-reported measure of general interest in politics.
24
Table 30 - Distribution of frequencies, Interest
Frequency Percent Valid Percent Cumulative Percent
Valid
Not at all interested 3266 13.8 14.1 14.1
Not very interested 5525 23.4 23.8 37.9
Somewhat interested 7967 33.7 34.4 72.3
Very interested 6434 27.2 27.7 100.0
Total 23192 98.2 100.0
Missing
DK 216 .9 REF 22 .1 999 191 .8 Total 429 1.8
Total 23621 100.0
3.3.1.8 Group activity
This binary variable derives from questions about being an active member of any type of voluntary
groups (political, religious, civic associations, …). People who reported to be active members in at
least one group have been coded as active members.
Table 31 - Distribution of frequencies, Group activity
Frequency Percent Valid Percent Cumulative Percent
Valid
Not an active member 10883 46.1 46.1 46.1
Active member 12706 53.8 53.9 100.0
Total 23589 99.9 100.0
Missing System 32 .1
Total 23621 100.0
3.3.2 Exposure and categorical variables
Tables 32-36 show the results of Pearson’s Chi-square tests for cross-tabulation of Exposure by
categorical variables such as Gender, Location, Group activity, Country, and Marital status.
Table 32 - Cross-tabulation and Chi-Square test, Exposure by Gender
Sex of the respondent
Total Male Female
Exposure to at least
one governance
programme
Not
reached
Count 7735 8140 15875
Expected Count 8151.6 7723.4 15875
% within Exposure to at least one
governance programme 48.7% 51.3% 100.0%
Regularly
reached
Count 2356 1421 3777
Expected Count 1939.4 1837.6 3777
% within Exposure to at least one
governance programme 62.4% 37.6% 100.0%
Total
Count 10091 9561 19652
Expected Count 10091 9561 19652
% within Exposure to at least one
governance programme 51.3% 48.7% 100.0%
Chi-Square Tests
Value df Asymp. Sig.
(2-sided)
Pearson Chi-Square 227.664a 1 < 0.001
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is
1837.57.
25
Table 33 - Cross-tabulation and Chi-Square test, Exposure by Location
Location Total
Rural Urban
Exposure to at least
one governance
programme
Not
reached
Count 10025 5850 15875
Expected Count 10024.4 5850.6 15875
% within Exposure to at least one
governance programme 63.1% 36.9% 100.0%
Regularly
reached
Count 2385 1393 3778
Expected Count 2385.6 1392.4 3778
% within Exposure to at least one
governance programme 63.1% 36.9% 100.0%
Total
Count 12410 7243 19653
Expected Count 12410 7243 19653
% within Exposure to at least one
governance programme 63.1% 36.9% 100.0%
Chi-Square Tests
Value df Asymp. Sig.
(2-sided)
Pearson Chi-Square 0.001 1 0.98
0 cells (0.0%) have expected count less than 5. The minimum expected count is
1392.36.
Table 34 - Cross-tabulation and Chi-Square test, Exposure by Group activity
Group activity (binary) Total
Not an active
member
Active
member
Exposure to at least
one governance
programme
Not
reached
Count 7639 8214 15853
Expected Count 7141.4 8711.6 15853
% within Exposure to at least one
governance programme 86.4% 76.2% 80.8%
Regularly
reached
Count 1203 2572 3775
Expected Count 1700.6 2074.4 3775
% within Exposure to at least one
governance programme 13.6% 23.8% 19.2%
Total
Count 8842 10786 19628
Expected Count 8842 10786 19628
% within Exposure to at least one
governance programme 100.0% 100.0% 100.0%
Chi-Square Tests
Value df Asymp. Sig.
(2-sided)
Pearson Chi-Square 328.002 1 < 0.001
0 cells (0.0%) have expected count less than 5. The minimum expected count is 1700.56.
26
Table 35 - Cross-tabulation and Chi-Square test, Exposure by Country
Country Total
Bangladesh Nepal Kenya Nigeria Tanzania Sierra
Leone Myanmar
Exposure
to at least
one
governance
programme
Not
reached
Count 1869 2307 2094 2630 3425 2559 991 15875
Expected Count 1691.5 2615.5 1881.3 3065.5 3069.5 2698.7 853.0 15875
% within Exposure to at
least one governance
programme
89.3% 71.2% 89.9% 69.3% 90.1% 76.6% 93.8% 80.8%
Regularly
reached
Count 225 931 235 1165 375 782 65 3778
Expected Count 402.5 622.5 447.7 729.5 730.5 642.3 203.0 3778
% within Exposure to at
least one governance
programme
10.7% 28.8% 10.1% 30.7% 9.9% 23.4% 6.2% 19.2%
Total
Count 2094 3238 2329 3795 3800 3341 1056 19653
Expected Count 2094 3238 2329 3795 3800 3341 1056 19653
% within Exposure to at
least one governance
programme
100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-
Square 1101.141 6 < 0.001
0 cells (0.0%) have expected count less than 5. The
minimum expected count is 203.00.
Table 36 - Cross-tabulation and Chi-Square test, Exposure by Marital status
Marital status Total
Single
Married,
living with
spouse
Married,
not living
with spouse
Divorced
/separated Widowed
In a
marriage
where the
husband has
more than
one wife
Living
with
partner
Exposure
to at least
one
governance
programme
Not
reached
Count 5179 8670 692 318 611 100 106 15676
Expected Count 5088.9 8755.7 713.5 291.4 558.5 157.4 110.6 15676
% within Exposure to
at least one
governance
programme
82.1% 79.9% 78.3% 88.1% 88.3% 51.3% 77.4% 80.7%
Regularly
reached
Count 1126 2178 192 43 81 95 31 3746
Expected Count 1216.1 2092.3 170.5 69.6 133.5 37.6 26.4 3746
% within Exposure to
at least one
governance
programme
17.9% 20.1% 21.7% 11.9% 11.7% 48.7% 22.6% 19.3%
Total
Count 6305 10848 884 361 692 195 137 19422
Expected Count 6305 10848 884 361 692 195 137 19422
% within Exposure to
at least one
governance
programme
100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson
Chi-Square 163.624 6 < 0.001
0 cells (0.0%) have expected count less than 5. The
minimum expected count is 26.42.
27
3.3.3 Exposure and ordinal variables
Table 37 shows the result of Matt-Whitney’s U-test for the association between Exposure and
ordinal variables such as Interest in politics, Age, Education, and Income.
Table 37 - Significance testing for Exposure and ordinal variables
Interest in politics Age in categories Education level Income
Not
reached Reached
Not
reached Reached
Not
reached Reached
Not
reached Reached
N 15687 3765 15860 3769 15543 3692 15291 3667
Mean rank 9198.6 11926 9751.78 10081.04 9213 11323 9391.88 9.844.85
Mann-Whitney U 37811888.5 30890889.5 34987282.5 29375788.5
Standard error 296593.407 303052.9 293538.319 242794.172
Standardised test
statistic 27.921 3.309 21.445 5.518
Asymptotic sig. (2-
sided test) < 0.001 0.001 < 0.001 < 0.001
3.4 Outcome variables – confounders
3.4.1 Participation
As described in the main report, Participation is significantly and positively associated to gender, age,
education, income, marital status, interest in politics and membership in groups.
3.4.1.1 Participation and categorical (binary) variables
Tables 38-40 report the results of t-tests where the difference in Participation means is analysed for
groups defined by binary variables such as gender, location, and membership in groups.
Table 38 - T-test results, Gender - Participation
Sex of the respondent N Mean Std.
Deviation
Std. Error
Mean
Average
political
participation
(0 to 10)
Male 11891 4.1550 2.19198 .02010
Female 11698 3.2692 1.87525 .01734
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
99% Confidence
Interval of the
Difference
Lower Upper
Equal
variances
assumed
496.947 < 0.001
33.326 23587 < 0.001 .88579 .02658 .81732 0.95426
Equal
variances
not
assumed
33.368 23142.228 < 0.001 .88579 .02655 .81741 0.95417
28
Table 39 - T-test results, Location - Participation
Location N Mean Std.
Deviation
Std. Error
Mean
Average
political
participation
(0 to 10)
Rural 15488 3.7882 2.06601 .01660
Urban 8102 3.5772 2.12402 .02360
Levene's Test
for Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
99% Confidence
Interval of the
Difference
Lower Upper
Equal
variances
assumed
1.415 .234
7.377 23588 < 0.001 .21099 .02860 .13731 0.28467
Equal
variances
not
assumed
7.313 16047.995 < 0.001 .21099 .02885 .13666 0.28531
Table 40 - T-test results, Group activity - Participation
Group activity N Mean Std.
Deviation
Std. Error
Mean
Average
political
participation
(0 to 10)
Not an
active
member
10854 3.0585 1.72183 .01653
Active
member 12705 4.2778 2.20516 .01956
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
99% Confidence
Interval of the
Difference
Lower Upper
Equal
variances
assumed
1218.71 < 0.001
-46.712 23557 < 0.001 -1.21932 .02610 -1.287 -1.152
Equal
variances
not
assumed
-47.611 23372.713 < 0.001 -1.21932 .02561 -1.285 -1.153
3.4.1.2 Participation and categorical variables
Tables 41-42 report mean scores and ANOVA for Participation, based on groups defined by
categorical variables such as country and marital status.
29
Table 41 - ANOVA for Participation, by Country
Average political
participation (0 to 10) N Mean
Std.
Deviation
Std.
Error
95% Confidence
Interval for Mean
Lower
Bound
Upper
Bound
Bangladesh 2650 3.2388 1.50744 .02928 3.1814 3.2963
Nepal 4000 3.3314 1.93867 .03065 3.2713 3.3914
Kenya 3002 4.6001 2.15373 .03931 4.5231 4.6772
Nigeria 4239 3.3922 2.26551 .03480 3.3240 3.4604
Tanzania 4111 3.3752 1.84620 .02879 3.3188 3.4317
Sierra Leone 4367 4.4461 2.23546 .03383 4.3798 4.5125
Myanmar 1221 3.4929 1.69080 .04839 3.3980 3.5879
Total 23590 3.7157 2.08847 .01360 3.6891 3.7424
Model
Fixed
Effects 2.01798 .01314 3.6900 3.7415
Random
Effects .23270 3.1463 4.2851
ANOVA
Sum of
Squares df
Mean
Square F Sig.
Between
Groups 6852.578 6 1142.096
280.458 < 0.001 Within
Groups 96036.102 23583 4.072
Total 102888.680 23589
Table 42 - ANOVA for Participation, by Marital Status
Average political
participation (0 to 10) N Mean
Std.
Deviation
Std.
Error
95% Confidence
Interval for Mean
Lower
Bound
Upper
Bound
Single 7298 3.2307 1.99696 .02338 3.1849 3.2765
Married, living with
spouse 13129 3.9099 2.06596 .01803 3.8746 3.9453
Married, not living with
spouse 1089 4.2354 2.19225 .06643 4.1050 4.3657
Divorced/separated 430 3.8234 2.11390 .10194 3.6230 4.0237
Widowed 951 3.6981 2.00756 .06510 3.5703 3.8258
In a marriage where the
husband has more than
one wife
226 5.3215 2.24953 .14964 5.0267 5.6164
Living with partner 173 3.8730 2.54996 .19387 3.4904 4.2557
Total 23296 3.7155 2.08699 .01367 3.6887 3.7423
Model
Fixed
Effects 2.05514 .01346 3.6891 3.7419
Random
Effects .30942 2.9584 4.4726
ANOVA
Sum of
Squares df
Mean
Square F Sig.
Between
Groups 3098.332 6 516.389
122.262 < 0.001 Within
Groups 98363.601 23289 4.224
Total 101461.933 23295
30
3.4.1.3 Participation and ordinal variables
Table 43 reports Spearman’s ρ correlation coefficients and their significance in a two-tailed
significance test. Participation is significantly associated with all of the four ordinal variables. The
association is positive in all cases except income.
Table 43 - Correlation coefficients for Participation and ordinal variables
Interest in
politics Age in categories Education level Income
Average political
participation (0 to
10)
Spearman's ρ 0.286 0.208 0.073 -0.075
Sig. (2-tailed) < 0.001 < 0.001 < 0.001 < 0.001
N 23186 23562 23074 22729
3.4.2 Knowledge
As described in the main report, bivariate analysis showed that Knowledge is associated with gender,
location, age, education, income, marital status, interest in politics and membership in groups.
3.4.2.1 Knowledge and categorical (binary) variables
Tables 44-46 report the results of t-tests where the difference in Knowledge average scores is
analysed for groups defined by binary variables such as gender, location, and membership in groups.
Table 44 - T-test results, Gender - Knowledge
Exposure to at least one
governance programme N Mean
Std.
Deviation
Std. Error
Mean
Average Self-
reported
knowledge (0
to 10)
Male 11724 5.0661 2.47966 .02290
Female 11305 4.4737 2.53391 .02383
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
99% Confidence
Interval of the
Difference
Lower Upper
Equal
variances
assumed
13.537 < 0.001
17.933 23027 < 0.001 .59247 .03304 .50736 0.67757
Equal
variances
not
assumed
17.926 22949.736 < 0.001 .59247 .03305 .50732 0.67761
31
Table 45 - T-test results, Location - Knowledge
Location N Mean Std.
Deviation
Std. Error
Mean
Average Self-
reported
knowledge (0
to 10)
Rural 15035 4.6306 2.48644 .02028
Urban 7995 5.0472 2.57077 .02875
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
99% Confidence
Interval of the
Difference
Lower Upper
Equal
variances
assumed
8.755 .003
-11.962 23028 < 0.001 -.41660 .03483 -.506 -0.327
Equal
variances
not
assumed
-11.841 15840.978 < 0.001 -.41660 .03518 -.507 -0.326
Table 46 - T-test results, Group activity - Knowledge
Group activity N Mean Std.
Deviation
Std. Error
Mean
Average Self-
reported
knowledge (0
to 10)
Not an
active
member
10439 4.3486 2.51740 .02464
Active
member 12565 5.1304 2.47277 .02206
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
99% Confidence
Interval of the
Difference
Lower Upper
Equal
variances
assumed
15.958 < 0.001
-23.678 23002 < 0.001 -.78178 .03302 -.867 -0.697
Equal
variances
not
assumed
-23.639 22088.002 < 0.001 -.78178 .03307 -.867 -0.697
3.4.2.2 Knowledge and categorical variables
Tables 47-48 report mean scores and ANOVA for Knowledge, based on groups defined by
categorical variables such as country and marital status.
32
Table 47 - ANOVA for Knowledge, by Country
Average Self-reported
knowledge (0 to 10) N Mean
Std.
Deviation
Std.
Error
95% Confidence
Interval for Mean
Lower
Bound
Upper
Bound
Bangladesh 2507 4.8710 2.67833 .05349 4.7661 4.9759
Nepal 3850 4.9613 1.91733 .03090 4.9007 5.0219
Kenya 2984 5.2149 2.44447 .04475 5.1272 5.3027
Nigeria 4193 5.1149 2.78798 .04306 5.0305 5.1993
Tanzania 4097 4.5550 2.45998 .03843 4.4796 4.6303
Sierra Leone 4186 4.6125 2.64102 .04082 4.5324 4.6925
Myanmar 1213 3.0363 2.02621 .05818 2.9221 3.1504
Total 23030 4.7752 2.52378 .01663 4.7426 4.8078
Model
Fixed
Effects 2.47901 .01634 4.7432 4.8072
Random
Effects .20504 4.2735 5.2769
ANOVA
Sum of
Squares df
Mean
Square F Sig.
Between
Groups 5194.840 6 865.807
140.885 < 0.001 Within
Groups 141487.895 23023 6.146
Total 146682.735 23029
Table 48 - ANOVA for Knowledge, by Marital Status
Average Self-reported
knowledge (0 to 10) N Mean
Std.
Deviation
Std.
Error
95% Confidence
Interval for Mean
Lower
Bound
Upper
Bound
Single 7179 4.7504 2.64019 .03116 4.6893 4.8115
Married, living with
spouse 12760 4.8233 2.44178 .02162 4.7810 4.8657
Married, not living with
spouse 1070 4.9924 2.51128 .07677 4.8417 5.1430
Divorced/separated 429 4.4365 2.55624 .12342 4.1939 4.6791
Widowed 924 4.0405 2.51010 .08258 3.8784 4.2025
In a marriage where the
husband has more than
one wife
223 5.4931 2.77941 .18612 5.1263 5.8599
Living with partner 159 5.0742 2.53338 .20091 4.6774 5.4710
Total 22744 4.7775 2.52458 .01674 4.7447 4.8103
Model
Fixed
Effects 2.51827 .01670 4.7448 4.8102
Random
Effects .15230 4.4048 5.1501
ANOVA
Sum of
Squares df
Mean
Square F Sig.
Between
Groups 761.503 6 126.917
20.013 < 0.001 Within
Groups 144190.704 22737 6.342
Total 144952.207 22743
33
3.4.2.3 Knowledge and ordinal variables
Table 49 reports Spearman’s ρ correlation coefficients and their significance in a two-tailed
significance test. Knowledge is significantly associated with all of the four variables, although the
correlation is very weak with Age. Interest is moderately correlated with Knowledge, while the
correlation is weak for Education and even weaker for Income. All of the correlations are positive.
Table 49 - Correlation coefficients for Knowledge and ordinal variables
Interest in
politics Age in categories Education level Income
Average Self-
reported knowledge
(0 to 10)
Spearman's ρ 0.334 0.024 0.267 0.122
Sig. (2-tailed) < 0.001 < 0.001 < 0.001 < 0.001
N 22713 23002 22519 22180
3.4.3 Discussion
As described in the main report, bivariate analysis showed that Discussion is associated with gender,
location, education, income, marital status, interest in politics and membership in groups.
3.4.3.1 Discussion and categorical (binary) variables
Tables 50-52 report the results of t-tests where the difference in Discussion average scores is
analysed for groups defined by binary variables such as gender, location, and membership in groups.
Table 50 - T-test results, Gender - Discussion
Exposure to at least one
governance programme N Mean
Std.
Deviation
Std. Error
Mean
Average
discussion
frequency (0
to 10)
Male 11816 4.9674 2.76922 .02548
Female 11581 4.1046 2.80766 .02609
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
99% Confidence
Interval of the
Difference
Lower Upper
Equal
variances
assumed
69.798 < 0.001
23.664 23395 < 0.001 .86278 .03646 .76886 0.95670
Equal
variances
not
assumed
23.661 23368.188 < 0.001 .86278 .03646 .76884 0.95671
34
Table 51 - T-test results, Location - Discussion
Location N Mean Std.
Deviation
Std. Error
Mean
Average
discussion
frequency (0
to 10)
Rural 15332 4.4033 2.84177 .02295
Urban 8066 4.8010 2.76365 .03077
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
99% Confidence
Interval of the
Difference
Lower Upper
Equal
variances
assumed
50.443 < 0.001
-10.272 23396 < 0.001 -.39775 .03872 -.498 -0.298
Equal
variances
not
assumed
-10.361 16798.447 < 0.001 -.39775 .03839 -.497 -0.299
Table 52 - T-test results, Group activity - Discussion
Group activity N Mean Std.
Deviation
Std. Error
Mean
Average
discussion
frequency (0
to 10)
Not an
active
member
10712 3.6561 2.72636 .02634
Active
member 12657 5.2920 2.67855 .02381
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
99% Confidence
Interval of the
Difference
Lower Upper
Equal
variances
assumed
38.916 < 0.001
-46.140 23367 < 0.001 -1.63590 .03545 -1.727 -1.545
Equal
variances
not
assumed
-46.072 22596.560 < 0.001 -1.63590 .03551 -1.727 -1.544
3.4.3.2 Discussion and categorical variables
Tables 53-54 report mean scores and ANOVA for Discussion, based on groups defined by
categorical variables such as country and marital status.
35
Table 53 - ANOVA for Discussion, by Country
Average discussion
frequency (0 to 10) N Mean
Std.
Deviation
Std.
Error
95% Confidence
Interval for Mean
Lower
Bound
Upper
Bound
Bangladesh 2635 2.9972 2.27356 .04429 2.9103 3.0840
Nepal 3967 4.1202 2.60827 .04141 4.0391 4.2014
Kenya 3000 5.1956 2.58111 .04712 5.1032 5.2880
Nigeria 4226 5.0487 2.70572 .04162 4.9671 5.1303
Tanzania 4106 4.7954 3.07903 .04805 4.7012 4.8896
Sierra Leone 4265 5.4177 2.60040 .03982 5.3397 5.4958
Myanmar 1199 1.8967 2.18122 .06299 1.7731 2.0203
Total 23398 4.5404 2.82137 .01844 4.5042 4.5765
Model
Fixed
Effects 2.65559 .01736 4.5064 4.5744
Random
Effects .41178 3.5328 5.5480
ANOVA
Sum of
Squares df
Mean
Square F Sig.
Between
Groups 21285.220 6 3547.537
503.042 < 0.001 Within
Groups 164957.377 23391 7.052
Total 186242.597 23397
Table 54 - ANOVA for Discussion, by Marital Status
Average discussion
frequency (0 to 10) N Mean
Std.
Deviation
Std.
Error
95% Confidence
Interval for Mean
Lower
Bound
Upper
Bound
Single 7265 4.6536 2.73961 .03214 4.5906 4.7166
Married, living with
spouse 13009 4.4667 2.81428 .02467 4.4183 4.5150
Married, not living with
spouse 1077 5.0433 2.85043 .08686 4.8729 5.2138
Divorced/separated 430 4.5872 3.05922 .14753 4.2972 4.8772
Widowed 944 3.5231 2.85366 .09288 3.3409 3.7054
In a marriage where the
husband has more than
one wife
224 6.7857 2.92928 .19572 6.4000 7.1714
Living with partner 160 4.8021 2.93549 .23207 4.3437 5.2604
Total 23109 4.5408 2.82043 .01855 4.5044 4.5772
Model
Fixed
Effects 2.80113 .01843 4.5047 4.5769
Random
Effects .28094 3.8534 5.2282
ANOVA
Sum of
Squares df
Mean
Square F Sig.
Between
Groups 2554.316 6 425.719
54.257 < 0.001 Within
Groups 181265.856 23102 7.846
Total 183820.172 23108
36
3.4.3.3 Discussion and ordinal variables
Table 55 reports Spearman’s ρ correlation coefficients and their significance in a two-tailed
significance test. Discussion is significantly associated with Interest, Education, and Income, although
its correlation with the latter is very weak. The association is positive in all cases. Discussion is not
correlated with age.
Table 55 - Correlation coefficients for Discussion and ordinal variables
Interest in
politics Age in categories Education level Income
Average discussion
frequency (0 to 10)
Spearman's ρ 0.287 -0.004 0.211 0.048
Sig. (2-tailed) < 0.001 0.269 < 0.001 < 0.001
N 23043 23370 22887 22547
3.4.4 Efficacy
As described in the main report, bivariate analysis showed that Efficacy is associated with gender,
location, age, education, income, marital status, interest in politics and membership in groups.
3.4.4.1 Efficacy and categorical (binary) variables
Tables 56-57 report the results of t-tests where the difference in Efficacy average scores is analysed
for groups defined by binary variables such as gender, location, and membership in groups.
Table 56 - T-test results, Gender - Efficacy
Exposure to at least one
governance programme N Mean
Std.
Deviation
Std. Error
Mean
Efficacy (0 to
10)
Male 11744 5.4965 1.88177 .01736
Female 11381 5.3683 1.92414 .01804
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
99% Confidence
Interval of the
Difference
Lower Upper
Equal
variances
assumed
5.209 .022
5.122 23123 < 0.001 .12819 .02503 .06372 0.19266
Equal
variances
not
assumed
5.120 23056.638 < 0.001 .12819 .02504 .06370 0.19269
37
Table 57 - T-test results, Location - Efficacy
Location N Mean Std.
Deviation
Std. Error
Mean
Efficacy (0 to
10)
Rural 8034 5.1995 1.94903 .02174
Urban 15092 5.5578 1.86738 .01520
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
99% Confidence
Interval of the
Difference
Lower Upper
Equal
variances
assumed
26.047 < 0.001
-13.680 23124 < 0.001 -.35823 .02619 -.426 -0.291
Equal
variances
not
assumed
-13.503 15794.561 < 0.001 -.35823 .02653 -.427 -0.290
Table 58 - T-test results, Group activity - Efficacy
Group activity N Mean Std.
Deviation
Std. Error
Mean
Efficacy (0 to
10)
Not an
active
member
10477 5.4857 1.95323 .01908
Active
member 12626 5.3900 1.86089 .01656
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
99% Confidence
Interval of the
Difference
Lower Upper
Equal
variances
assumed
24.426 < 0.001
3.807 23101 < 0.001 .09576 .02515 .03097 0.16056
Equal
variances
not
assumed
3.790 21893.795 < 0.001 .09576 .02527 .03067 0.16085
3.4.4.2 Efficacy and categorical variables
Tables 59-60 report mean scores and ANOVA for Efficacy, based on groups defined by categorical
variables such as country and marital status.
38
Table 59 - ANOVA for Efficacy, by Country
Efficacy (0 to 10) N Mean Std.
Deviation
Std.
Error
95% Confidence
Interval for Mean
Lower
Bound
Upper
Bound
Bangladesh 2591 6.2951 2.05842 .04044 6.2158 6.3744
Nepal 3897 5.4621 1.34724 .02158 5.4198 5.5044
Kenya 3003 5.6782 1.67673 .03060 5.6182 5.7382
Nigeria 4205 4.7405 1.99119 .03071 4.6803 4.8007
Tanzania 4100 5.4216 1.94450 .03037 5.3620 5.4811
Sierra Leone 4241 5.1140 1.95129 .02996 5.0553 5.1727
Myanmar 1089 6.5675 1.67598 .05079 6.4679 6.6672
Total 23126 5.4333 1.90376 .01252 5.4088 5.4578
Model
Fixed
Effects 1.83506 .01207 5.4097 5.4570
Random
Effects .21999 4.8950 5.9716
ANOVA
Sum of
Squares df
Mean
Square F Sig.
Between
Groups 5959.882 6 993.314
294.975 < 0.001 Within
Groups 77852.174 23119 3.367
Total 83812.056 23125
Table 60 - ANOVA for Efficacy, by Marital Status
Efficacy (0 to 10) N Mean Std.
Deviation
Std.
Error
95% Confidence
Interval for Mean
Lower
Bound
Upper
Bound
Single 7193 5.2688 1.91970 .02263 5.2244 4.8115
Married, living with
spouse 12867 5.5592 1.89128 .01667 5.5265 4.8657
Married, not living with
spouse 1071 5.1664 1.84978 .05652 5.0554 5.1430
Divorced/separated 422 5.5125 1.95418 .09513 5.3255 4.6791
Widowed 897 5.4832 1.88203 .06284 5.3599 4.2025
In a marriage where the
husband has more than
one wife
226 5.2099 1.85296 .12326 4.9670 5.8599
Living with partner 168 5.0499 1.58404 .12221 4.8087 5.4710
Total 22844 5.4383 1.90243 .01259 5.4136 4.8103
Model
Fixed
Effects 1.89674 .01255 5.4137 4.8102
Random
Effects .12588 5.1303 5.1501
ANOVA
Sum of
Squares df
Mean
Square F Sig.
Between
Groups 515.229 6 85.872
23.869 < 0.001 Within
Groups 82159.295 22837 3.598
Total 82674.525 22843
39
3.4.4.3 Efficacy and ordinal variables
Table 61 reports Spearman’s ρ correlation coefficients and their significance in a two-tailed
significance test. Efficacy is significantly associated with all of the four variables except Income. The
correlation is positive and weak with Interest, and positive and very weak with age. Efficacy is
negatively and very weakly associated with Education.
Table 61 - Correlation coefficients for Efficacy and ordinal variables
Interest in
politics Age in categories Education level Income
Efficacy (0 to 10)
Spearman's ρ 0.155 0.069 -0.033 -0.007
Sig. (2-tailed) < 0.001 < 0.001 < 0.001 0.139
N 22824 23098 22627 22288
40
4 Multivariate regression analysis
This section details the process undertaken to build multivariate regression models to evaluate the
relationship between exposure to BBC Media Action programming and outcomes variables
(Participation, Discussion, Knowledge, and Efficacy). As described in the previous sections, we
defined the outcome variables (see Section 2), the hypothesised explanatory variable (Exposure, see
section 3.1.1), and confounders (see Section 3.3.1) and tested their mutual associations (see Section
3).
OLS regression models assessed the association between the predictors and the construct
outcomes. Categorical and ordinal confounders were introduced into the model as dummy variables,
with a single dummy for each ‘level’ or ‘category’ apart from the reference category.
For each categorical confounder, we set the reference category as that with the largest number of
cases. This is the case of Gender (Male is the reference category since it has 11904 cases, i.e. 50.4%
of total), Location (Rural = 15503, i.e. 65.6% of total), and Marital status (“Married, living with
spouse” = 13132, i.e. 55.6%). Also the Country variable’s reference category is the largest sized
(Sierra Leone = 4389 cases, i.e. 18.6% of total).
For ordinal confounders (Age, Education, and Interest in politics), the reference category is the
lowest one. For Income we set the “Medium” level as the reference category, since it is the largest
(15041, i.e. 63.7% of total) and also the most common from a conceptual point of view.
For Group activity, the reference category is “Not an active member”.
For each of the outcome variables, we developed four OLS models. The first includes Exposure as
the hypothesised explanatory variable and the full list of confounders (Gender, Age, Location,
Education, Income, Marital status, Interest in politics, and Group activity), together with the Country
variable. We introduced the predictors in three blocks in order to observe the change in R2 and F.
We introduced Exposure in the first block, socio-political confounders (Interest in politics and
Group activity) in the second one, and demographic confounders in the third one (Gender, Age,
Location, Education, Income, Marital status), together with the Country variable.
The second model includes the interaction between Exposure and Gender. We are particularly
interested in checking whether the association between Exposure and the outcomes is significantly
different for men and women, so we built specific models to test this. For these models, we included
the Gender variable together with the interaction term (Exposure for Women) as a second block,
after Exposure. Socio-political confounders were included as a third block and demographic
confounders (included Country) as a fourth one.
The third model includes all of the interaction terms that proved to be significant. At this stage, we
tested for significance of interactions between the Exposure variable and all of the confounders
(both socio-political and demographic). We included all the interactions that remained significant in a
single model, where we included Exposure as a first block, each interaction term with the
corresponding confounders as a single block, and the all the confounders that do not interact
significantly with Exposure as a last block.
The fourth model includes only interactions with the Country variable. This is specifically aimed at
checking whether the main results are consistent across countries. In this case we included
41
Exposure as the first block, the interaction terms and the country dummies as the second one, the
socio-political confounders as the third one, and the demographic confounders as the fourth one.
For each of the above described model we report in this appendix:
a model summary, including:
- the R, the R2, and the adjusted R2 of the model,
- the standard error of the estimate,
- the R2 and the F changes, their degrees of freedom, and the significance of the F change.
ANOVA table, including:
- the total, model’s and residual Sum of Squares,
- the mean square,
- the F-value and its significance.
coefficients’ table, including:
- B coefficients and their standard errors,
- standardised Beta coefficients,
- t-statistics,
- significance values,
- 99% confidence intervals of the B coefficients,
- tolerance and Variance Inflation Factors (VIFs).
a diagnostics section, including:
- model’s number of cases, outliers (standardised residuals > |3|) and influential cases
(Cook’s distance > |1|);
- model’s Durbin-Watson statistic;
- a scatterplot of the model’s standardised residuals against their predicted values.
Table 62 - List of regression models
Outcome
variable
Model n. 1
(no interactions)
Model n. 2
(interaction with
Gender)
Model n. 3
(interaction with
other confounders)
Model n. 4
(interaction with
Country)
Participation 4.1.1 4.1.2 4.1.3 4.1.4
Knowledge 4.2.1 4.2.2 4.2.3 4.2.4
Discussion 4.3.1 4.3.2 4.3.3 4.3.4
Efficacy 4.4.1 4.4.2 4.4.3 4.4.4
42
4.1 Regression models – Participation
4.1.1 Model n. 1 – Exposure with all confounders
4.1.1.1 Model summary
The model includes 23621 observations. Missing data were handled using pair-wise deletion. 18320
cases have no missing data.
Table 63 - Model n. 1 summary - Participation
Model R R2 Adjusted
R2
Std. Error of
the Estimate
Change Statistics
R2
Change F Change df1 df2
Sig. F
Change
1 0.188 0.035 0.035 2.051 0.035 694.622 1 18956 < 0.001
2 0.398 0.158 0.158 1.917 0.123 690.582 4 18952 < 0.001
3 0.538 0.289 0.288 1.762 0.131 139.471 25 18927 < 0.001
4.1.1.2 ANOVA
Table 64 – Model n. 1 ANOVA - Participation
Model Sum of
Squares df
Mean
Square F Sig.
1
Regression 2922.807 1 2922.807 694.622 < 0.001
Residual 79762.372 18956 4.208
Total 82685.180 18957
2
Regression 13069.555 5 2613.911 711.605 < 0.001
Residual 69615.625 18952 3.673
Total 82685.180 18957
3
Regression 23899.267 30 796.642 256.491 < 0.001
Residual 58785.912 18927 3.106
Total 82685.180 18957
4.1.1.3 Coefficients
Significance testing was conducted using the parameters test and an examination of the t-statistic in
the parameter estimate tables.
Multicollinearity testing was conducted and all variables were acceptable, with a tolerance statistic
well above 0.2 for all variables and an average Variance Inflation Factor (VIF) of 1.643.
43
Table 65 - Model n. 1 regression coefficients - Participation
Coefficients
t Sig.
99% Confidence
Interval for B Collinearity Statistics
B Std. Error Beta Lower
Bound
Upper
Bound Tolerance VIF
(Constant) 2.828 .071 39.726 < 0.001 2.645 3.012
Exposure to at least one governance
programme .530 .035 .100 15.175 < 0.001 .440 .620 .865 1.156
Sex of the respondent – Female -.550 .027 -.132 -20.303 < 0.001 -.620 -.481 .892 1.121
Group activity (binary) – Active members .804 .031 .192 26.169 < 0.001 .725 .883 .699 1.430
Interest in politics - Not very interested .264 .043 .054 6.074 < 0.001 .152 .376 .478 2.094
Interest in politics - Somewhat interested .687 .042 .156 16.406 < 0.001 .579 .795 .414 2.414
Interest in politics - Very interested 1.267 .045 .272 28.191 < 0.001 1.151 1.383 .405 2.471
Country - Bangladesh -.567 .056 -.086 -10.210 < 0.001 -.710 -.424 .534 1.874
Country - Nepal -1.204 .049 -.216 -24.779 < 0.001 -1.330 -1.079 .493 2.029
Country - Kenya .043 .049 .007 .866 .386 -.084 .170 .605 1.653
Country - Nigeria -.981 .046 -.180 -21.133 < 0.001 -1.100 -.861 .516 1.936
Country - Tanzania -1.033 .048 -.188 -21.484 < 0.001 -1.157 -.909 .492 2.031
Country - Myanmar -.532 .070 -.056 -7.647 < 0.001 -.711 -.353 .690 1.450
Location – Urban -.254 .030 -.058 -8.534 < 0.001 -.331 -.177 .819 1.221
Age groups - 25-34 .400 .037 .087 10.744 < 0.001 .304 .496 .573 1.744
Age groups - 35-44 .577 .045 .106 12.913 < 0.001 .462 .692 .561 1.783
Age groups - 45-54 .821 .051 .126 16.061 < 0.001 .690 .953 .614 1.628
Age groups - 55-64 .938 .061 .114 15.365 < 0.001 .780 1.095 .683 1.465
Age groups - 65+ 1.026 .071 .105 14.496 < 0.001 .844 1.208 .711 1.406
Education - Literate .217 .049 .035 4.382 < 0.001 .089 .344 .604 1.655
Education - Completed primary .411 .046 .081 8.848 < 0.001 .291 .531 .443 2.255
Education - Completed secondary .440 .045 .099 9.886 < 0.001 .326 .555 .372 2.687
Education - Completed college or university .792 .053 .137 14.896 < 0.001 .655 .929 .443 2.259
Income - Low (can afford food at most) .195 .034 .040 5.815 < 0.001 .109 .282 .777 1.287
Income - High (can afford almost
everything) -.011 .048 -.002 -0.239 .811 -.135 .112 .869 1.151
Marital Status - Single -.482 .037 -.107 -13.137 < 0.001 -.576 -.387 .566 1.767
Marital Status - Married, not living with
spouse -.073 .063 -.007 -1.163 .245 -.234 .088 .939 1.065
Marital Status - Divorced/Separated -.182 .097 -.012 -1.878 .060 -.432 .068 .961 1.040
Marital Status - Widowed -.097 .069 -.009 -1.409 .159 -.275 .081 .877 1.140
Marital Status - In a marriage where the
husband has more than on wife .735 .134 .034 5.491 < 0.001 .390 1.079 .953 1.049
Marital Status - Living with partner .035 .151 .001 .228 .820 -.355 .425 .970 1.031
4.1.1.4 Diagnostics
Table 66 - Model n. 1 diagnostics - Participation
N. of
cases
N.
predicted
scores
Std
residuals
> |3.29|
Std
residuals
> |2.58|
Std
residuals
> |1.96|
Cook's
distance
above |1|
Durbin-
Watson
statistic
23621 18320 0.26% 1.35% 5.45% 0.00% 1.643
44
Figure 9 - Residuals and predicted values - Model n. 1 - Participation
4.1.2 Model n. 2 – Exposure & Gender interaction
4.1.2.1 Model summary
Table 67 - Model n. 2 summary - Participation
Model R R2 Adjusted
R2
Std. Error of
the Estimate
Change Statistics
R2
Change F Change df1 df2
Sig. F
Change
1 0.188 0.035 0.035 2.051 0.035 694.622 1 18956 < 0.001
2 0.271 0.073 0.073 2.011 0.038 387.690 2 18954 < 0.001
3 0.429 0.184 0.184 1.887 0.111 643.902 4 18950 < 0.001
4 0.538 0.289 0.288 1.762 0.105 116.890 24 18926 < 0.001
45
4.1.2.2 ANOVA
Table 68 - Model n. 2 ANOVA - Participation
Model Sum of
Squares df
Mean
Square F Sig.
1
Regression 2922.807 1 2922.807 694.622 < 0.001
Residual 79762.372 18956 4.208
Total 82685.180 18957
2
Regression 6057.533 3 2019.178 499.448 < 0.001
Residual 76627.647 18954 4.043
Total 82685.180 18957
3
Regression 15226.282 7 2175.183 611.035 < 0.001
Residual 67458.898 18950 3.560
Total 82685.180 18957
4
Regression 23934.711 31 772.087 248.722 < 0.001
Residual 58750.469 18926 3.104
Total 82685.180 18957
4.1.2.3 Coefficients
Significance testing was conducted using the parameters test and an examination of the t-statistic in
the parameter estimate tables.
Multicollinearity testing was conducted and all variables were acceptable, with a tolerance statistic
well above 0.2 for all variables and an average Variance Inflation Factor (VIF) of 1.680.
46
Table 69 - Model n. 2 regression coefficients - Participation
Coefficients
t Sig.
99% Confidence
Interval for B Collinearity Statistics
B Std. Error Beta Lower
Bound
Upper
Bound Tolerance VIF
(Constant) 2.809 .071 39.338 < 0.001 2.625 2.993
Exposure to at least one governance
programme .621 .044 .117 14.067 < 0.001 .507 .735 .541 1.850
Sex of the respondent – Female -.509 .030 -.122 -17.119 < 0.001 -.586 -.432 .741 1.350
Exposure for women -.237 .070 -.028 -3.379 .001 -.418 -.056 .545 1.836
Group activity – Active members .803 .031 .192 26.143 < 0.001 .724 .882 .699 1.431
Interest in politics - Not very interested .269 .043 .055 6.182 < 0.001 .157 .381 .477 2.096
Interest in politics - Somewhat interested .693 .042 .158 16.539 < 0.001 .585 .801 .413 2.419
Interest in politics - Very interested 1.269 .045 .272 28.244 < 0.001 1.153 1.385 .405 2.472
Country - Bangladesh -.573 .056 -.087 -10.321 < 0.001 -.716 -.430 .533 1.876
Country - Nepal -1.213 .049 -.218 -24.929 < 0.001 -1.338 -1.088 .492 2.034
Country - Kenya .042 .049 .007 .841 .400 -.086 .169 .605 1.653
Country - Nigeria -.978 .046 -.180 -21.085 < 0.001 -1.098 -.859 .516 1.937
Country - Tanzania -1.032 .048 -.187 -21.472 < 0.001 -1.156 -.909 .492 2.031
Country - Myanmar -.531 .070 -.056 -7.632 < 0.001 -.710 -.351 .690 1.450
Location – Urban -.255 .030 -.058 -8.560 < 0.001 -.332 -.178 .819 1.221
Age groups - 25-34 .398 .037 .087 10.697 < 0.001 .302 .494 .573 1.744
Age groups - 35-44 .573 .045 .105 12.826 < 0.001 .458 .688 .560 1.784
Age groups - 45-54 .816 .051 .125 15.966 < 0.001 .685 .948 .614 1.629
Age groups - 55-64 .935 .061 .114 15.322 < 0.001 .778 1.092 .683 1.465
Age groups - 65+ 1.027 .071 .105 14.515 < 0.001 .845 1.209 .711 1.406
Education - Literate .215 .049 .034 4.349 < 0.001 .088 .342 .604 1.655
Education - Completed primary .409 .046 .081 8.805 < 0.001 .289 .529 .443 2.255
Education - Completed secondary .438 .045 .099 9.835 < 0.001 .323 .553 .372 2.688
Education - Completed college or university .790 .053 .137 14.857 < 0.001 .653 .927 .443 2.259
Income - Low (can afford food at most) .193 .034 .040 5.748 < 0.001 .107 .280 .777 1.287
Income - High (can afford almost
everything) -.011 .048 -.002 -0.237 .813 -.135 .112 .869 1.151
Marital Status - Single -.482 .037 -.107 -13.142 < 0.001 -.576 -.387 .566 1.767
Marital Status - Married, not living with
spouse -.071 .063 -.007 -1.129 .259 -.232 .091 .939 1.065
Marital Status - Divorced/Separated -.187 .097 -.012 -1.929 .054 -.437 .063 .961 1.041
Marital Status - Widowed -.102 .069 -.010 -1.472 .141 -.279 .076 .877 1.141
Marital Status - In a marriage where the
husband has more than on wife .728 .134 .034 5.440 < 0.001 .383 1.072 .953 1.049
Marital Status - Living with partner .026 .151 .001 .171 .864 -.364 .416 .970 1.031
4.1.2.4 Diagnostics
Table 70 - Model n. 2 diagnostics - Participation
N. of
cases
N.
predicted
scores
Std
residuals
> |3.29|
Std
residuals
> |2.58|
Std
residuals
> |1.96|
Cook's
distance
above |1|
Durbin-
Watson
statistic
23621 18320 0.26% 1.36% 5.53% 0.00% 1.642
47
Figure 10 - Residuals and predicted values - Model n. 2 - Participation
4.1.3 Model n. 3 – Exposure & significant interactions
4.1.3.1 Model summary
Table 71 - Model n. 3 summary - Participation
Model R R2 Adjusted
R2
Std. Error of
the Estimate
Change Statistics
R2
Change F Change df1 df2
Sig. F
Change
1 .188a 0.035 0.035 2.051 0.035 694.622 1 18956 < 0.001
2 .271b 0.073 0.073 2.011 0.038 387.690 2 18954 < 0.001
3 .333c 0.111 0.111 1.970 0.038 80.752 10 18944 < 0.001
4 .360d 0.129 0.128 1.950 0.018 49.237 8 18936 < 0.001
5 .434e 0.188 0.187 1.883 0.059 690.689 2 18934 < 0.001
6 .476f 0.227 0.226 1.838 0.038 157.076 6 18928 < 0.001
7 .542g 0.294 0.292 1.757 0.067 119.178 15 18913 < 0.001
48
4.1.3.2 ANOVA
Table 72 - Model n. 3 ANOVA - Participation
Model Sum of
Squares df
Mean
Square F Sig.
1
Regression 2922.807 1 2922.807 694.622 < 0.001
Residual 79762.372 18956 4.208
Total 82685.180 18957
2
Regression 6057.533 3 2019.178 499.448 < 0.001
Residual 76627.647 18954 4.043
Total 82685.180 18957
3
Regression 9190.377 13 706.952 182.224 < 0.001
Residual 73494.803 18944 3.880
Total 82685.180 18957
4
Regression 10688.010 21 508.953 133.860 < 0.001
Residual 71997.170 18936 3.802
Total 82685.180 18957
5
Regression 15583.575 23 677.547 191.183 < 0.001
Residual 67101.605 18934 3.544
Total 82685.180 18957
6
Regression 18766.209 29 647.111 191.626 < 0.001
Residual 63918.971 18928 3.377
Total 82685.180 18957
7
Regression 24286.123 44 551.957 178.756 < 0.001
Residual 58399.057 18913 3.088
Total 82685.180 18957
4.1.3.3 Coefficients
Significance testing was conducted using the parameters test and an examination of the t-statistic in
the parameter estimate tables.
Multicollinearity testing revealed that, apart from Exposure and its interactions, all variables were
acceptable, with a tolerance statistic well above 0.2 for all variables. The average Variance Inflation
Factor (VIF) is 3.289.
49
Table 73 - Model n. 3 regression coefficients - Participation
Coefficients
t Sig.
99% Confidence
Interval for B
Collinearity
Statistics
B Std. Error Beta Lower
Bound
Upper
Bound Tolerance VIF
(Constant) 2.558 .078 32.826 < 0.001 2.357 2.758
Exposure to at least one governance
programme 1.985 .175 .375 11.359 < 0.001 1.535 2.435 .034 29.119
Sex of the respondent – Women -.492 .030 -.118 -16.485 < 0.001 -.569 -.415 .732 1.365
Exposure for women -.309 .072 -.037 -4.288 < 0.001 -.494 -.123 .513 1.948
Age groups - 25-34 .450 .042 .098 10.698 < 0.001 .342 .558 .446 2.242
Exposure for 25-34 -.228 .094 -.024 -2.417 .016 -.472 .015 .368 2.716
Age groups - 35-44 .674 .050 .123 13.442 < 0.001 .544 .803 .444 2.255
Exposure for 35-44 -0.428 .109 -.036 -3.910 < 0.001 -0.710 -0.146 .448 2.231
Age groups - 45-54 .887 .058 .136 15.320 < 0.001 .738 1.036 .477 2.097
Exposure for 45-54 -0.289 .125 -.020 -2.300 .021 -0.612 0.035 .497 2.013
Age groups - 55-64 1.017 .068 .124 14.901 < 0.001 .841 1.192 .543 1.841
Exposure for 55-64 -.325 .159 -.016 -2.045 .041 -0.735 .085 .612 1.633
Age groups - 65+ 1.139 .077 .117 14.709 < 0.001 0.940 1.338 .591 1.693
Exposure for 65 or more -.526 .207 -.018 -2.542 .011 -1.059 .007 .709 1.410
Education - Literate .261 .056 .042 4.687 < 0.001 0.117 .404 .474 2.109
Exposure for Literate -.152 .166 -.009 -0.915 .360 -0.578 .275 .361 2.774
Education - Completed primary .507 .052 .100 9.766 < 0.001 0.374 .641 .353 2.835
Exposure for Primary -.447 .152 -.032 -2.938 .003 -0.839 -.055 .310 3.226
Education - Completed secondary .567 .051 .128 11.027 < 0.001 0.435 .699 .277 3.604
Exposure for Secondary -.560 .136 -.067 -4.108 < 0.001 -0.912 -.209 .142 7.041
Education - Completed college or university .886 .062 .154 14.261 < 0.001 0.726 1.046 .322 3.104
Exposure for High educated -.456 .148 -.044 -3.081 .002 -0.837 -.075 .182 5.491
Group activity – Active members .737 .034 .176 21.794 < 0.001 0.650 .824 .573 1.744
Exposure for Active members .296 .075 .046 3.972 < 0.001 0.104 .489 .280 3.572
Interest in politics - Not very interested .419 .048 .085 8.685 < 0.001 0.295 .543 .386 2.590
Exposure for Not very interested -1.231 .175 -.092 -7.050 < 0.001 -1.681 -.781 .218 4.596
Interest in politics - Somewhat interested .822 .047 .187 17.349 < 0.001 .700 .944 .322 3.105
Exposure for Somewhat interested -1.025 .164 -.117 -6.259 < 0.001 -1.447 -.603 .106 9.437
Interest in politics - Very interested 1.382 .052 .296 26.736 < 0.001 1.249 1.515 .304 3.287
Exposure for Very interested -.967 .167 -.121 -5.800 < 0.001 -1.397 -.538 .085 11.732
Country - Bangladesh -.563 .056 -.085 -10.108 < 0.001 -.706 -.419 .528 1.894
Country - Nepal -1.209 .049 -.217 -24.843 < 0.001 -1.334 -1.083 .489 2.045
Country - Kenya .050 .049 .008 1.010 .313 -.077 0.177 .603 1.658
Country - Nigeria -.978 .046 -.180 -21.046 < 0.001 -1.098 -.858 .512 1.953
Country - Tanzania -1.004 .048 -.182 -20.829 < 0.001 -1.129 -.880 .487 2.053
Country - Myanmar -.520 .070 -.055 -7.447 < 0.001 -.700 -.340 .679 1.472
Location – Urban -.242 .030 -.055 -8.149 < 0.001 -.319 -.166 .816 1.226
Income - Low (can afford food at most) .165 .034 .034 4.890 < 0.001 .078 .251 .769 1.300
Income - High (can afford almost everything) -.006 .048 -.001 -0.131 .896 -.130 .117 .869 1.151
Marital Status - Single -.467 .037 -.104 -12.729 < 0.001 -.562 -.373 .562 1.781
Marital Status - Married, not living with spouse -.069 .062 -.007 -1.103 .270 -.230 .092 .938 1.066
Marital Status - Divorced/Separated -.184 .097 -.012 -1.897 .058 -.433 .066 .960 1.042
Marital Status - Widowed -.110 .069 -.010 -1.590 .112 -.287 .068 .873 1.145
Marital Status - In a marriage where the husband
has more than on wife .629 .136 .030 4.626 < 0.001 .279 0.980 .916 1.091
Marital Status - Living with partner .023 .151 .001 .151 .880 -.366 .412 .969 1.032
50
4.1.3.4 Diagnostics
Table 74 - Model n. 3 diagnostics - Participation
N. of
cases
N.
predicted
scores
Std
residuals
> |3.29|
Std
residuals
> |2.58|
Std
residuals
> |1.96|
Cook's
distance
above |1|
Durbin-
Watson
statistic
23621 18320 0.28% 1.48% 5.73% 0.00% 1.642
Figure 11 - Residuals and predicted values - Model n. 3 - Participation
4.1.4 Model n. 4 – Exposure & Country interactions
4.1.4.1 Model summary
Table 75 - Model n. 4 summary - Participation
Model R R2 Adjusted
R2
Std. Error of
the Estimate
Change Statistics
R2
Change F Change df1 df2
Sig. F
Change
1 0.188 0.035 0.035 2.051 0.035 694.622 1 18956 < 0.001
2 0.331 0.110 0.109 1.971 0.074 131.879 12 18944 < 0.001
3 0.465 0.216 0.216 1.850 0.107 643.499 4 18940 < 0.001
4 0.54 0.291 0.290 1.760 0.075 105.252 19 18921 < 0.001
51
4.1.4.2 ANOVA
Table 76 - Model n. 4 ANOVA - Participation
Model Sum of
Squares df
Mean
Square F Sig.
1
Regression 2922.807 1 2922.807 694.622 < 0.001
Residual 79762.372 18956 4.208
Total 82685.180 18957
2
Regression 9072.281 13 697.868 179.594 < 0.001
Residual 73612.899 18944 3.886
Total 82685.180 18957
3
Regression 17879.544 17 1051.738 307.379 < 0.001
Residual 64805.636 18940 3.422
Total 82685.180 18957
4
Regression 24074.216 36 668.728 215.881 < 0.001
Residual 58610.963 18921 3.098
Total 82685.180 18957
4.1.4.3 Coefficients
Significance testing was conducted using the parameters test and an examination of the t-statistic in
the parameter estimate tables.
Multicollinearity testing revealed that Exposure is the only variable with Tolerance level below 0.2,
which is due to its interactions with the country categories. The average Variance Inflation Factor
(VIF) is 1.934.
52
Table 77 - Model n. 4 regression coefficients - Participation
Coefficients
t Sig.
99% Confidence
Interval for B
Collinearity
Statistics
B Std. Error Beta Lower
Bound
Upper
Bound Tolerance VIF
(Constant) 2.964 .074 39.916 < 0.001 2.773 3.155
Exposure to at least one governance
programme .112 .077 .021 1.458 .145 -.086 .310 .178 5.625
Country - Bangladesh -.678 .061 -.102 -11.099 < 0.001 -.835 -.520 .440 2.272
Exposure for Bangladesh .318 .161 .015 1.977 .048 -.096 .733 .652 1.533
Country - Nepal -1.392 .058 -.250 -24.132 < 0.001 -1.541 -1.244 .349 2.866
Exposure for Nepal .693 .113 .066 6.133 < 0.001 .402 .984 .328 3.052
Country - Kenya -.053 .055 -.008 -0.965 .335 -.194 .088 .489 2.043
Exposure for Kenya .241 .157 .012 1.529 .126 -.165 .646 .651 1.536
Country - Nigeria -1.174 .056 -.216 -21.088 < 0.001 -1.317 -1.030 .358 2.792
Exposure for Nigeria .701 .108 .073 6.470 < 0.001 .422 .979 .292 3.425
Country - Tanzania -1.151 .054 -.209 -21.398 < 0.001 -1.290 -1.013 .392 2.549
Exposure for Tanzania .384 .135 .023 2.838 .005 .035 .732 .564 1.772
Country - Myanmar -.656 .074 -.070 -8.847 < 0.001 -.847 -.465 .605 1.654
Exposure for Myanmar .432 .265 .011 1.632 .103 -.250 1.113 .844 1.184
Group activity – Active members .800 .031 .191 26.050 < 0.001 .721 .879 .698 1.433
Interest in politics - Not very interested .252 .044 .051 5.796 < 0.001 .140 .364 .475 2.104
Interest in politics - Somewhat interested .683 .042 .155 16.269 < 0.001 .575 .791 .411 2.434
Interest in politics - Very interested 1.261 .045 .270 28.038 < 0.001 1.145 1.377 .403 2.482
Sex of the respondent – Female -.545 .027 -.130 -20.083 < 0.001 -.615 -.475 .888 1.126
Location – Urban -.253 .030 -.057 -8.460 < 0.001 -.329 -.176 .813 1.230
Age groups - 25-34 .401 .037 .087 10.781 < 0.001 .305 .496 .573 1.744
Age groups - 35-44 .576 .045 .106 12.910 < 0.001 .461 .691 .560 1.784
Age groups - 45-54 .821 .051 .126 16.082 < 0.001 .690 .953 .614 1.628
Age groups - 55-64 .940 .061 .114 15.428 < 0.001 .783 1.098 .682 1.465
Age groups - 65+ 1.034 .071 .106 14.626 < 0.001 .852 1.216 .711 1.406
Education - Literate .216 .049 .034 4.366 < 0.001 .088 .343 .602 1.661
Education - Completed primary .403 .047 .080 8.653 < 0.001 .283 .523 .441 2.270
Education - Completed secondary .434 .045 .098 9.708 < 0.001 .319 .549 .368 2.715
Education - Completed college or university .782 .053 .136 14.646 < 0.001 .645 .920 .438 2.285
Income - Low (can afford food at most) .183 .034 .038 5.434 < 0.001 .096 .269 .775 1.291
Income - High (can afford almost everything) -.018 .048 -.002 -0.367 .714 -.141 .106 .868 1.152
Marital Status - Single -.486 .037 -.108 -13.271 < 0.001 -.581 -0.392 .565 1.769
Marital Status - Married, not living with spouse -.075 .062 -.008 -1.201 .230 -.236 0.086 .939 1.065
Marital Status - Divorced/Separated -.185 .097 -.012 -1.913 .056 -.435 .064 .961 1.041
Marital Status - Widowed -.095 .069 -.009 -1.379 .168 -.273 .083 .877 1.141
Marital Status - In a marriage where the husband
has more than on wife .828 .135 .039 6.155 < 0.001 .481 1.175 .940 1.064
Marital Status - Living with partner .043 .151 .002 .287 .774 -.346 .433 .970 1.031
4.1.4.4 Diagnostics
Table 78 - Model n. 4 diagnostics - Participation
N. of
cases
N.
predicted
scores
Std
residuals
> |3.29|
Std
residuals
> |2.58|
Std
residuals
> |1.96|
Cook's
distance
above |1|
Durbin-
Watson
statistic
23621 18320 0.25% 1.38% 5.48% 0.00% 1.646
53
Figure 12 - Residuals and predicted values - Model n. 4 - Participation
54
4.2 Regression models – Knowledge
4.2.1 Model n. 1 – Exposure with all confounders
4.2.1.1 Model summary
The model includes 23621 observations. Missing data were handled using pair wise deletion. 18320
cases have no missing data.
Table 79 - Model n. 1 summary - Knowledge
Model R R2 Adjusted
R2
Std. Error of
the Estimate
Change Statistics
R2
Change F Change df1 df2
Sig. F
Change
1 0.212 0.045 0.045 2.466 0.045 894.832 1 18956 < 0.001
2 0.378 0.143 0.143 2.336 0.098 542.636 4 18952 < 0.001
3 0.463 0.215 0.213 2.238 0.071 68.819 25 18927 < 0.001
4.2.1.2 ANOVA
Table 80 - Model n. 1 ANOVA - Knowledge
Model Sum of
Squares df
Mean
Square F Sig.
1
Regression 5442.977 1 5442.977 894.832 < 0.001
Residual 115303.239 18956 6.083
Total 120746.216 18957
2
Regression 17291.491 5 3458.298 633.530 < 0.001
Residual 103454.726 18952 5.459
Total 120746.216 18957
3
Regression 25911.948 30 863.732 172.383 < 0.001
Residual 94834.268 18927 5.011
Total 120746.216 18957
4.2.1.3 Coefficients
Significance testing was conducted using the parameters test and an examination of the t-statistic in
the parameter estimate tables.
Multicollinearity testing was conducted and all variables were acceptable, with a tolerance statistic
well above 0.2 for all variables and an average Variance Inflation Factor (VIF) of 1.643.
55
Table 81 - Model n. 1 regression coefficients - Knowledge
Coefficients
t Sig.
99% Confidence
Interval for B
Collinearity
Statistics
B Std. Error Beta Lower
Bound
Upper
Bound Tolerance VIF
(Constant) 2.353 .090 26.023 < 0.001 2.120 2.586
Exposure to at least one governance
programme .653 .044 .102 14.721 < 0.001 .539 .767 .865 1.156
Sex of the respondent – Female -.166 .034 -.033 -4.829 < 0.001 -.255 -.078 .892 1.121
Group activity – Active members .311 .039 .061 7.969 < 0.001 .210 .411 .699 1.430
Interest in politics - Not very interested .603 .055 .102 10.924 < 0.001 .461 .746 .478 2.094
Interest in politics - Somewhat interested 1.313 .053 .247 24.685 < 0.001 1.176 1.450 .414 2.414
Interest in politics - Very interested 2.033 .057 .361 35.615 < 0.001 1.886 2.180 .405 2.471
Country - Bangladesh .686 .071 .086 9.725 < 0.001 .504 .867 .534 1.874
Country - Nepal 0.105 .062 .016 1.694 .090 -0.054 0.264 .493 2.029
Country - Kenya .270 .063 .036 4.297 < 0.001 .108 .431 .605 1.653
Country - Nigeria .116 .059 .018 1.971 .049 -0.036 .268 .516 1.936
Country - Tanzania -.269 .061 -.040 -4.398 < 0.001 -0.426 -.111 .492 2.031
Country - Myanmar -1.216 .088 -.107 -13.768 < 0.001 -1.443 -.988 .690 1.450
Location – Urban .119 .038 .022 3.151 .002 .022 .217 .819 1.221
Age groups - 25-34 .231 .047 .042 4.898 < 0.001 .110 .353 .573 1.744
Age groups - 35-44 .364 .057 .055 6.417 < 0.001 .218 .510 .561 1.783
Age groups - 45-54 .364 .065 .046 5.602 < 0.001 .197 .531 .614 1.628
Age groups - 55-64 .402 .078 .040 5.189 < 0.001 .203 0.602 .683 1.465
Age groups - 65+ .385 .090 .033 4.286 < 0.001 .154 0.617 .711 1.406
Education - Literate .416 .063 .055 6.627 < 0.001 .254 .578 .604 1.655
Education - Completed primary .629 .059 .103 10.653 < 0.001 .477 .781 .443 2.255
Education - Completed secondary 1.007 .057 .188 17.811 < 0.001 .862 1.153 .372 2.687
Education - Completed college or university 1.680 .068 .241 24.883 < 0.001 1.506 1.854 .443 2.259
Income - Low (can afford food at most) -.034 .043 -.006 -0.787 .431 -.143 .076 .777 1.287
Income - High (can afford almost everything) .144 .061 .016 2.369 .018 -.013 .301 .869 1.151
Marital Status - Single -.128 .047 -.024 -2.756 .006 -.248 -.008 .566 1.767
Marital Status - Married, not living with spouse -.035 .079 -.003 -.443 .658 -.240 .169 .939 1.065
Marital Status - Divorced/Separated -.196 .123 -.010 -1.592 .111 -.514 .121 .961 1.040
Marital Status - Widowed -.149 .088 -.012 -1.702 .089 -.375 .077 .877 1.140
Marital Status - In a marriage where the husband
has more than on wife .857 .170 .033 5.045 < 0.001 .419 1.295 .953 1.049
Marital Status - Living with partner .489 .192 .017 2.541 .011 -.007 .984 .970 1.031
4.2.1.4 Diagnostics
Table 82 - Model n. 1 diagnostics - Knowledge
N. of
cases
N.
predicted
scores
Std
residuals
> |3.29|
Std
residuals
> |2.58|
Std
residuals
> |1.96|
Cook's
distance
above |1|
Durbin-
Watson
statistic
23621 18320 0.00% 0.56% 5.15% 0.00% 1.616
56
Figure 13 - Residuals and predicted values - Model n. 1 - Knowledge
4.2.2 Model n. 2 – Exposure & Gender interaction
4.2.2.1 Model summary
Table 83 - Model n. 2 summary - Knowledge
Model R R2 Adjusted
R2
Std. Error of
the Estimate
Change Statistics
R2
Change F Change df1 df2
Sig. F
Change
1 0.212 0.045 0.045 2.466 0.045 894.832 1 18956 < 0.001
2 0.378 0.143 0.143 2.336 0.098 542.636 4 18952 < 0.001
3 0.463 0.215 0.213 2.238 0.071 68.819 25 18927 < 0.001
57
4.2.2.2 ANOVA
Table 84 - Model n. 2 ANOVA - Knowledge
Model Sum of
Squares df
Mean
Square F Sig.
1
Regression 5442.977 1 5442.977 894.832 < 0.001
Residual 115303.239 18956 6.083
Total 120746.216 18957
2
Regression 6534.235 3 2178.078 361.462 < 0.001
Residual 114211.981 18954 6.026
Total 120746.216 18957
3
Regression 17626.923 7 2518.132 462.751 < 0.001
Residual 103119.293 18950 5.442
Total 120746.216 18957
4
Regression 25912.372 31 835.883 166.817 < 0.001
Residual 94833.844 18926 5.011
Total 120746.216 18957
4.2.2.3 Coefficients
Significance testing was conducted using the parameters test and an examination of the t-statistic in
the parameter estimate tables.
Multicollinearity testing was conducted and all variables were acceptable, with a tolerance statistic
well above 0.2 for all variables and an average Variance Inflation Factor (VIF) of 1.682.
58
Table 85 - Model n. 2 regression coefficients - Knowledge
Coefficients
t Sig.
99% Confidence
Interval for B
Collinearity
Statistics
B Std. Error Beta Lower
Bound
Upper
Bound Tolerance VIF
(Constant) 2.356 .091 25.957 < 0.001 2.122 2.589
Exposure to at least one governance
programme .643 .056 .100 11.417 < 0.001 .498 .788 .537 1.862
Sex of the respondent – Female -.171 .038 -.034 -4.494 < 0.001 -.269 -.073 .731 1.368
Exposure*Sex - Exposure for women .026 .089 .003 0.291 .771 -.204 .256 .536 1.865
Group activity – Active members .311 .039 .061 7.971 < 0.001 .210 .411 .699 1.431
Interest in politics - Not very interested .603 .055 .102 10.909 < 0.001 .460 .745 .477 2.096
Interest in politics - Somewhat interested 1.312 .053 .247 24.650 < 0.001 1.175 1.450 .413 2.419
Interest in politics - Very interested 2.033 .057 .361 35.607 < 0.001 1.886 2.180 .405 2.472
Country - Bangladesh .687 .071 .086 9.729 < 0.001 .505 .868 .533 1.877
Country - Nepal 0.106 .062 .016 1.707 .088 -0.054 0.265 .492 2.035
Country - Kenya .270 .063 .036 4.298 < 0.001 .108 .431 .605 1.653
Country - Nigeria .116 .059 .018 1.966 .049 -0.036 .268 .516 1.937
Country - Tanzania -.269 .061 -.040 -4.399 < 0.001 -0.426 -.111 .492 2.031
Country - Myanmar -1.216 .088 -.107 -13.766 < 0.001 -1.443 -.988 .690 1.450
Location – Urban .119 .038 .022 3.153 .002 .022 .217 .819 1.221
Age groups - 25-34 .232 .047 .042 4.901 < 0.001 .110 .353 .573 1.744
Age groups - 35-44 .365 .057 .055 6.422 < 0.001 .218 .511 .560 1.784
Age groups - 45-54 .364 .065 .046 5.608 < 0.001 .197 .532 .614 1.629
Age groups - 55-64 .402 .078 .040 5.192 < 0.001 .203 0.602 .683 1.465
Age groups - 65+ .385 .090 .033 4.284 < 0.001 .153 0.617 .711 1.406
Education - Literate .416 .063 .055 6.630 < 0.001 .254 .578 .604 1.655
Education - Completed primary .629 .059 .103 10.656 < 0.001 .477 .781 .443 2.255
Education - Completed secondary 1.008 .057 .188 17.813 < 0.001 .862 1.153 .372 2.688
Education - Completed college or university 1.681 .068 .241 24.884 < 0.001 1.507 1.855 .443 2.259
Income - Low (can afford food at most) -.033 .043 -.006 -0.782 .434 -.143 .077 .777 1.287
Income - High (can afford almost everything) .144 .061 .016 2.368 .018 -.013 .301 .869 1.151
Marital Status - Single -.128 .047 -.024 -2.756 .006 -.248 -.008 .566 1.767
Marital Status - Married, not living with spouse -.036 .079 -.003 -.447 .655 -.240 .169 .939 1.065
Marital Status - Divorced/Separated -.196 .123 -.010 -1.588 .112 -.513 .122 .961 1.041
Marital Status - Widowed -.149 .088 -.012 -1.697 .090 -.375 .077 .877 1.140
Marital Status - In a marriage where the husband
has more than on wife .858 .170 .033 5.048 < 0.001 .420 1.296 .953 1.049
Marital Status - Living with partner .489 .192 .017 2.545 .011 -.006 .985 .970 1.031
4.2.2.4 Diagnostics
Table 86 - Model n. 2 diagnostics - Knowledge
N. of
cases
N.
predicted
scores
Std
residuals
> |3.29|
Std
residuals
> |2.58|
Std
residuals
> |1.96|
Cook's
distance
above |1|
Durbin-
Watson
statistic
23621 18320 0.00% 0.56% 5.13% 0.00% 1.616
59
Figure 14 - Residuals and predicted values - Model n. 2 - Knowledge
4.2.3 Model n. 3 – Exposure & significant interactions
4.2.3.1 Model summary
Table 87 - Model n. 3 summary - Knowledge
Model R R2 Adjusted
R2
Std. Error of
the Estimate
Change Statistics
R2
Change F Change df1 df2
Sig. F
Change
1 0.212 0.045 0.045 2.466 0.045 894.832 1 18956 < 0.001
2 0.221 0.049 0.048 2.462 0.004 7.184 10 18946 < 0.001
3 0.35 0.123 0.122 2.365 0.074 199.513 8 18938 < 0.001
4 0.448 0.201 0.200 2.258 0.078 307.718 6 18932 < 0.001
5 0.45 0.203 0.201 2.255 0.002 11.632 4 18928 < 0.001
6 0.479 0.230 0.228 2.218 0.027 44.330 15 18913 < 0.001
60
4.2.3.2 ANOVA
Table 88 - Model n. 3 ANOVA - Knowledge
Model Sum of
Squares df
Mean
Square F Sig.
1
Regression 5442.977 1 5442.977 894.832 < 0.001
Residual 115303.239 18956 6.083
Total 120746.216 18957
2
Regression 5878.520 11 534.411 88.144 < 0.001
Residual 114867.696 18946 6.063
Total 120746.216 18957
3
Regression 14807.112 19 779.322 139.314 < 0.001
Residual 105939.104 18938 5.594
Total 120746.216 18957
4
Regression 24220.583 25 968.823 190.020 < 0.001
Residual 96525.633 18932 5.099
Total 120746.216 18957
5
Regression 24457.279 29 843.354 165.782 < 0.001
Residual 96288.937 18928 5.087
Total 120746.216 18957
6
Regression 27727.637 44 630.174 128.130 < 0.001
Residual 93018.579 18913 4.918
Total 120746.216 18957
4.2.3.3 Coefficients
Significance testing was conducted using the parameters test and an examination of the t-statistic in
the parameter estimate tables.
Multicollinearity testing revealed that, apart from Exposure and its interactions, all variables were
acceptable, with a tolerance statistic well above 0.2 for all variables. The average Variance Inflation
Factor (VIF) is 3.224.
61
Table 89 - Model n. 3 regression coefficients - Knowledge
Coefficients
t Sig.
99% Confidence
Interval for B
Collinearity
Statistics
B Std. Error Beta Lower
Bound
Upper
Bound Tolerance VIF
(Constant) 1.743 .098 17.771 < 0.001 1.491 1.996
Exposure to at least one governance
programme 3.984 .214 .622 18.636 < 0.001 3.433 4.534 .037 27.352
Sex of the respondent – Female -.153 .034 -.030 -4.492 < 0.001 -.241 -.065 .890 1.123
Age groups - 25-34 .298 .053 .054 5.623 < 0.001 .162 .435 .447 2.240
Exposure for 25-34 -.221 .119 -.019 -1.855 .064 -.527 .086 .370 2.703
Age groups - 35-44 .516 .063 .078 8.163 < 0.001 .353 .678 .444 2.250
Exposure for 35-44 -.522 .137 -.036 -3.801 < 0.001 -.876 -.168 .453 2.208
Age groups - 45-54 .554 .073 .070 7.594 < 0.001 .366 .742 .478 2.093
Exposure for 45-54 -.689 .157 -.039 -4.392 < 0.001 -1.094 -.285 .506 1.978
Age groups - 55-64 .585 .086 .059 6.807 < 0.001 .364 .807 .544 1.837
Exposure for 55-64 -.644 .199 -.026 -3.232 .001 -1.157 -.131 .623 1.606
Age groups - 65+ .601 .098 .051 6.163 < 0.001 .350 .853 .592 1.688
Exposure for 65 or more -.733 .260 -.021 -2.822 .005 -1.401 -.064 .717 1.394
Education - Literate .625 .070 .083 8.893 < 0.001 .444 .806 .473 2.115
Exposure for Literate -1.128 .209 -.057 -5.391 < 0.001 -1.667 -.589 .360 2.778
Education - Completed primary .958 .066 .157 14.562 < 0.001 .789 1.128 .350 2.855
Exposure for Primary -1.781 .193 -.106 -9.210 < 0.001 -2.279 -1.282 .306 3.269
Education - Completed secondary 1.377 .065 .257 21.052 < 0.001 1.208 1.545 .273 3.661
Exposure for Secondary -1.806 .176 -.178 -10.274 < 0.001 -2.259 -1.353 .136 7.339
Education - Completed college or university 2.118 .079 .304 26.641 < 0.001 1.913 2.323 .314 3.189
Exposure for High educated -2.070 .195 -.166 -10.620 < 0.001 -2.572 -1.568 .167 5.983
Group activity – Active members .285 .039 .056 7.357 < 0.001 .185 .384 .697 1.434
Interest in politics - Not very interested .883 .061 .149 14.508 < 0.001 .726 1.040 .386 2.592
Exposure for Not very interested -2.358 .221 -.146 -10.658 < 0.001 -2.928 -1.788 .216 4.631
Interest in politics - Somewhat interested 1.524 .060 .287 25.523 < 0.001 1.370 1.678 .323 3.100
Exposure for Somewhat interested -1.840 .207 -.174 -8.896 < 0.001 -2.373 -1.307 .106 9.445
Interest in politics - Very interested 2.201 .065 .390 33.802 < 0.001 2.033 2.369 .305 3.276
Exposure for Very interested -1.672 .210 -.174 -7.966 < 0.001 -2.212 -1.131 .086 11.664
Country - Bangladesh .752 .070 .094 10.713 < 0.001 .571 .932 .529 1.889
Country - Nepal .140 .061 .021 2.287 .022 -.018 .298 .490 2.040
Country - Kenya .269 .062 .036 4.325 < 0.001 .109 .430 .603 1.659
Country - Nigeria .112 .059 .017 1.911 .056 -.039 .263 .512 1.955
Country - Tanzania -.189 .061 -.028 -3.100 .002 -.345 -.032 .487 2.054
Country - Myanmar -1.168 .088 -.103 -13.274 < 0.001 -1.394 -.941 .682 1.466
Location – Urban .138 .038 .026 3.682 < 0.001 .042 .235 .815 1.227
Income - Low (can afford food at most) -.164 .047 -.028 -3.513 < 0.001 -.284 -.044 .638 1.568
Exposure for Low income .479 .115 .035 4.162 < 0.001 .182 .775 .578 1.729
Income - High (can afford almost everything) .106 .071 .012 1.498 .134 -.076 .287 .636 1.572
Exposure for High income .239 .142 .014 1.680 .093 -.128 .606 .580 1.725
Marital Status - Single -.097 .046 -.018 -2.088 .037 -.216 .023 .561 1.781
Marital Status - Married, not living with spouse -.044 .079 -.004 -.564 .573 -.247 .158 .938 1.066
Marital Status - Divorced/Separated -.186 .122 -.010 -1.525 .127 -.501 .128 .960 1.042
Marital Status - Widowed -.159 .087 -.012 -1.823 .068 -.383 .066 .874 1.145
Marital Status - In a marriage where the husband
has more than on wife .465 .172 .018 2.704 .007 .022 0.908 .913 1.095
Marital Status - Living with partner .460 .191 .016 2.413 .016 -.031 .951 .969 1.032
4.2.3.4 Diagnostics
Table 90 - Model n. 3 diagnostics - Knowledge
N. of
cases
N.
predicted
scores
Std
residuals
> |3.29|
Std
residuals
> |2.58|
Std
residuals
> |1.96|
Cook's
distance
above |1|
Durbin-
Watson
statistic
23621 18320 0.01% 0.74% 5.32% 0.00% 1.623
62
Figure 15 - Residuals and predicted values - Model n. 3 - Knowledge
4.2.4 Model n. 4 – Exposure & Country interactions
4.2.4.1 Model summary
Table 91 - Model n. 4 summary - Knowledge
Model R R2 Adjusted
R2
Std. Error of
the Estimate
Change Statistics
R2
Change F Change df1 df2
Sig. F
Change
1 0.212 0.045 0.045 2.466 0.045 894.832 1 18956 < 0.001
2 0.28 0.079 0.078 2.424 0.033 57.274 12 18944 < 0.001
3 0.418 0.175 0.174 2.293 0.096 553.673 4 18940 < 0.001
4 0.467 0.218 0.216 2.234 0.043 54.372 19 18921 < 0.001
63
4.2.4.2 ANOVA
Table 92 - Model n. 4 ANOVA - Knowledge
Model Sum of
Squares df
Mean
Square F Sig.
1
Regression 5442.977 1 5442.977 894.832 < 0.001
Residual 115303.239 18956 6.083
Total 120746.216 18957
2
Regression 9479.734 13 729.21 124.154 < 0.001
Residual 111266.482 18944 5.873
Total 120746.216 18957
3
Regression 21128.254 17 1242.838 236.296 < 0.001
Residual 99617.962 18940 5.260
Total 120746.216 18957
4
Regression 26285.744 36 730.160 146.255 < 0.001
Residual 94460.472 18921 4.992
Total 120746.216 18957
4.2.4.3 Coefficients
Significance testing was conducted using the parameters test and an examination of the t-statistic in
the parameter estimate tables.
Multicollinearity testing revealed that Exposure is the only variable with Tolerance level below 0.2,
which is due to its interactions with the country categories. The average Variance Inflation Factor
(VIF) is 1.934.
64
Table 93 - Model n. 4 regression coefficients - Knowledge
Coefficients
t Sig.
99% Confidence
Interval for B
Collinearity
Statistics
B Std. Error Beta Lower
Bound
Upper
Bound Tolerance VIF
(Constant) 2.167 .094 22.986 < 0.001 1.924 2.410
Exposure to at least one governance
programme 1.247 .098 .195 12.767 < 0.001 .995 1.499 .178 5.625
Country - Bangladesh .834 .078 .104 10.762 < 0.001 .634 1.034 .440 2.272
Exposure for Bangladesh -.331 .204 -.013 -1.619 .106 -.858 .196 .652 1.533
Country - Nepal .420 .073 .062 5.739 < 0.001 .232 .609 .349 2.866
Exposure for Nepal -1.157 .143 -.091 -8.069 < 0.001 -1.527 -.788 .328 3.052
Country - Kenya .439 .070 .058 6.299 < 0.001 .259 .618 .489 2.043
Exposure for Kenya -.753 .200 -.030 -3.772 < 0.001 -1.268 -.239 .651 1.536
Country - Nigeria .269 .071 .041 3.805 < 0.001 .087 .451 .358 2.792
Exposure for Nigeria -.620 .137 -.054 -4.512 < 0.001 -.974 -.266 .292 3.425
Country - Tanzania -.061 .068 -.009 -0.888 .375 -.237 .115 .392 2.549
Exposure for Tanzania -.955 .172 -.048 -5.564 < 0.001 -1.397 -.513 .564 1.772
Country - Myanmar -1.049 .094 -.092 -11.140 < 0.001 -1.291 -.806 .605 1.654
Exposure for Myanmar -.420 .336 -.009 -1.250 .211 -1.285 .445 .844 1.184
Group activity – Active members .322 .039 .064 8.253 < 0.001 .221 .422 .698 1.433
Interest in politics - Not very interested .606 .055 .102 10.960 < 0.001 .463 .748 .475 2.104
Interest in politics - Somewhat interested 1.295 .053 .244 24.280 < 0.001 1.157 1.432 .411 2.434
Interest in politics - Very interested 2.021 .057 .358 35.386 < 0.001 1.874 2.168 .403 2.482
Sex of the respondent – Female -.178 .034 -.035 -5.171 < 0.001 -.267 -.089 .888 1.126
Location – Urban .126 .038 .024 3.336 .001 .029 .224 .813 1.230
Age groups - 25-34 .229 .047 .041 4.859 < 0.001 .108 .351 .573 1.744
Age groups - 35-44 .371 .057 .056 6.544 < 0.001 .225 .517 .560 1.784
Age groups - 45-54 .366 .065 .046 5.652 < 0.001 .199 .533 .614 1.628
Age groups - 55-64 .401 .077 .040 5.184 < 0.001 .202 .601 .682 1.465
Age groups - 65+ .378 .090 .032 4.216 < 0.001 .147 .609 .711 1.406
Education - Literate .419 .063 .055 6.671 < 0.001 .257 .580 .602 1.661
Education - Completed primary .647 .059 .106 10.949 < 0.001 .495 .800 .441 2.270
Education - Completed secondary 1.029 .057 .192 18.136 < 0.001 .883 1.175 .368 2.715
Education - Completed college or university 1.708 .068 .245 25.188 < 0.001 1.533 1.882 .438 2.285
Income - Low (can afford food at most) -.022 .043 -.004 -0.507 .612 -.132 .088 .775 1.291
Income - High (can afford almost everything) .161 .061 .018 2.639 .008 .004 .317 .868 1.152
Marital Status - Single -.123 .047 -.023 -2.642 .008 -.243 -0.003 .565 1.769
Marital Status - Married, not living with spouse -.033 .079 -.003 -0.414 .679 -.237 0.171 .939 1.065
Marital Status - Divorced/Separated -.195 .123 -.010 -1.587 .113 -.512 .122 .961 1.041
Marital Status - Widowed -.158 .088 -.012 -1.803 .071 -.383 .068 .877 1.141
Marital Status - In a marriage where the husband
has more than on wife .729 .171 .028 4.266 < 0.001 .289 1.169 .940 1.064
Marital Status - Living with partner .480 .192 .016 2.498 .012 -.015 .974 .970 1.031
4.2.4.4 Diagnostics
Table 94 - Model n. 4 diagnostics - Knowledge
N. of
cases
N.
predicted
scores
Std
residuals
> |3.29|
Std
residuals
> |2.58|
Std
residuals
> |1.96|
Cook's
distance
above |1|
Durbin-
Watson
statistic
23621 18320 0.00% 0.58% 5.19% 0.00% 1.62
65
Figure 16 - Residuals and predicted values - Model n. 4 - Knowledge
66
4.3 Regression models – Discussion
4.3.1 Model n. 1 – Exposure with all confounders
4.3.1.1 Model summary
The model includes 23621 observations. Missing data were handled using pair wise deletion. 18320
cases have no missing data.
Table 95 - Model n. 1 summary - Discussion
Model R R2 Adjusted
R2
Std. Error of
the Estimate
Change Statistics
R2
Change F Change df1 df2
Sig. F
Change
1 0.188 0.035 0.035 2.051 0.035 694.622 1 18956 < 0.001
2 0.398 0.158 0.158 1.917 0.123 690.582 4 18952 < 0.001
3 0.538 0.289 0.288 1.762 0.131 139.471 25 18927 < 0.001
4.3.1.2 ANOVA
Table 96 - Model n. 1 ANOVA - Discussion
Model Sum of
Squares df
Mean
Square F Sig.
1
Regression 2922.807 1 2922.807 694.622 < 0.001
Residual 79762.372 18956 4.208
Total 82685.180 18957
2
Regression 13069.555 5 2613.911 711.605 < 0.001
Residual 69615.625 18952 3.673
Total 82685.180 18957
3
Regression 23899.267 30 796.642 256.491 < 0.001
Residual 58785.912 18927 3.106
Total 82685.180 18957
4.3.1.3 Coefficients
Significance testing was conducted using the parameters test and an examination of the t-statistic in
the parameter estimate tables.
Multicollinearity testing was conducted and all variables were acceptable, with a tolerance statistic
well above 0.2 for all variables and an average Variance Inflation Factor (VIF) of 1.643.
67
Table 97 - Model n. 1 regression coefficients - Discussion
Coefficients
t Sig.
99% Confidence
Interval for B
Collinearity
Statistics
B Std. Error Beta Lower
Bound
Upper
Bound Tolerance VIF
(Constant) 3.618 .100 36.315 < 0.001 3.362 3.875
Exposure to at least one governance
programme .470 .049 .066 9.624 < 0.001 .344 .596 .865 1.156
Sex of the respondent – Female -.463 .038 -.082 -12.195 < 0.001 -.560 -.365 .892 1.121
Group activity – Active members .610 .043 .108 14.187 < 0.001 .499 .720 .699 1.430
Interest in politics - Not very interested .450 .061 .068 7.400 < 0.001 .293 .607 .478 2.094
Interest in politics - Somewhat interested 1.147 .059 .193 19.573 < 0.001 .996 1.298 .414 2.414
Interest in politics - Very interested 1.691 .063 .268 26.890 < 0.001 1.529 1.853 .405 2.471
Country - Bangladesh -1.873 .078 -.209 -24.101 < 0.001 -2.073 -1.672 .534 1.874
Country - Nepal -1.442 .068 -.192 -21.198 < 0.001 -1.617 -1.267 .493 2.029
Country - Kenya -.506 .069 -.060 -7.324 < 0.001 -.684 -.328 .605 1.653
Country - Nigeria -.586 .065 -.080 -9.024 < 0.001 -0.753 -.419 .516 1.936
Country - Tanzania -.729 .067 -.098 -10.825 < 0.001 -0.902 -.555 .492 2.031
Country - Myanmar -2.984 .097 -.234 -30.669 < 0.001 -3.235 -2.733 .690 1.450
Location – Urban -.022 .042 -.004 -0.539 .590 -.130 .085 .819 1.221
Age groups - 25-34 .220 .052 .035 4.222 < 0.001 .086 .354 .573 1.744
Age groups - 35-44 .336 .063 .046 5.377 < 0.001 .175 .497 .561 1.783
Age groups - 45-54 .392 .072 .044 5.475 < 0.001 .207 .576 .614 1.628
Age groups - 55-64 .311 .085 .028 3.638 < 0.001 .091 0.531 .683 1.465
Age groups - 65+ .265 .099 .020 2.672 .008 .010 0.520 .711 1.406
Education - Literate .229 .069 .027 3.306 .001 .051 .407 .604 1.655
Education - Completed primary .508 .065 .074 7.807 < 0.001 .340 .675 .443 2.255
Education - Completed secondary .811 .062 .135 13.009 < 0.001 .650 .971 .372 2.687
Education - Completed college or university 1.119 .074 .143 15.034 < 0.001 .927 1.310 .443 2.259
Income - Low (can afford food at most) -.139 .047 -.021 -2.949 .003 -.260 -.018 .777 1.287
Income - High (can afford almost everything) .004 .067 .000 0.063 .950 -.169 .177 .869 1.151
Marital Status - Single -.215 .051 -.035 -4.182 < 0.001 -.347 -.082 .566 1.767
Marital Status - Married, not living with spouse -.018 .088 -.001 -.209 .834 -.244 .207 .939 1.065
Marital Status - Divorced/Separated -.232 .136 -.011 -1.705 .088 -.581 .118 .961 1.040
Marital Status - Widowed -.423 .097 -.030 -4.381 < 0.001 -.672 -.174 .877 1.140
Marital Status - In a marriage where the husband
has more than on wife 1.459 .187 .051 7.795 < 0.001 .977 1.942 .953 1.049
Marital Status - Living with partner -.237 .212 -.007 -1.119 .263 -.783 .309 .970 1.031
4.3.1.4 Diagnostics
Table 98 - Model n. 1 diagnostics - Discussion
N. of
cases
N.
predicted
scores
Std
residuals
> |3.29|
Std
residuals
> |2.58|
Std
residuals
> |1.96|
Cook's
distance
above |1|
Durbin-
Watson
statistic
23621 18320 0.02% 0.48% 4.99% 0.00% 1.666
68
Figure 17 - Residuals and predicted values - Model n. 1 - Discussion
4.3.2 Model n. 2 – Exposure & Gender interaction
4.3.2.1 Model summary
Table 99 - Model n. 2 summary - Discussion
Model R R2 Adjusted
R2
Std. Error of
the Estimate
Change Statistics
R2
Change F Change df1 df2
Sig. F
Change
1 0.174 0.030 0.030 2.778 0.030 592.956 1 18956 < 0.001
2 0.221 0.049 0.049 2.752 0.018 183.511 2 18954 < 0.001
3 0.404 0.163 0.163 2.581 0.115 648.597 4 18950 < 0.001
4 0.487 0.237 0.236 2.466 0.074 76.230 24 18926 < 0.001
69
4.3.2.2 ANOVA
Table 100 - Model n. 2 ANOVA - Discussion
Model Sum of
Squares df
Mean
Square F Sig.
1
Regression 4577.069 1 4577.069 592.956 < 0.001
Residual 146322.657 18956 7.719
Total 150899.727 18957
2
Regression 7356.616 3 2452.205 323.799 < 0.001
Residual 143543.111 18954 7.573
Total 150899.727 18957
3
Regression 24642.158 7 3520.308 528.363 < 0.001
Residual 126257.568 18950 6.663
Total 150899.727 18957
4
Regression 35771.348 31 1153.914 189.692 < 0.001
Residual 115128.379 18926 6.083
Total 150899.727 18957
4.3.2.3 Coefficients
Significance testing was conducted using the parameters test and an examination of the t-statistic in
the parameter estimate tables.
Multicollinearity testing was conducted and all variables were acceptable, with a tolerance statistic
well above 0.2 for all variables and an average Variance Inflation Factor (VIF) of 1.682.
70
Table 101 - Model n. 2 regression coefficients - Discussion
Coefficients
t Sig.
99% Confidence
Interval for B
Collinearity
Statistics
B Std. Error Beta Lower
Bound
Upper
Bound Tolerance VIF
(Constant) 3.621 .100 36.210 < 0.001 3.363 3.878
Exposure to at least one governance
programme .460 .062 .064 7.417 < 0.001 .300 .620 .537 1.862
Sex of the respondent – Female -.467 .042 -.083 -11.152 < 0.001 -.575 -.359 .731 1.368
Exposure*Sex - Exposure for women .026 .098 .002 0.266 .791 -.227 .280 .536 1.865
Group activity – Active members .610 .043 .108 14.188 < 0.001 .499 .720 .699 1.431
Interest in politics - Not very interested .450 .061 .068 7.387 < 0.001 .293 .607 .477 2.096
Interest in politics - Somewhat interested 1.147 .059 .193 19.544 < 0.001 .995 1.298 .413 2.419
Interest in politics - Very interested 1.691 .063 .268 26.883 < 0.001 1.529 1.853 .405 2.472
Country - Bangladesh -1.872 .078 -.209 -24.075 < 0.001 -2.072 -1.672 .533 1.877
Country - Nepal -1.441 .068 -.192 -21.153 < 0.001 -1.617 -1.266 .492 2.035
Country - Kenya -.506 .069 -.060 -7.323 < 0.001 -.684 -.328 .605 1.653
Country - Nigeria -.586 .065 -.080 -9.027 < 0.001 -0.754 -.419 .516 1.937
Country - Tanzania -.729 .067 -.098 -10.825 < 0.001 -0.902 -.555 .492 2.031
Country - Myanmar -2.984 .097 -.234 -30.666 < 0.001 -3.235 -2.733 .690 1.450
Location – Urban -.022 .042 -.004 -0.537 .591 -.130 .085 .819 1.221
Age groups - 25-34 .220 .052 .035 4.225 < 0.001 .086 .354 .573 1.744
Age groups - 35-44 .337 .063 .046 5.382 < 0.001 .176 .498 .560 1.784
Age groups - 45-54 .392 .072 .044 5.480 < 0.001 .208 .577 .614 1.629
Age groups - 55-64 .311 .085 .028 3.641 < 0.001 .091 0.531 .683 1.465
Age groups - 65+ .264 .099 .020 2.671 .008 .009 0.520 .711 1.406
Education - Literate .229 .069 .027 3.309 .001 .051 .407 .604 1.655
Education - Completed primary .508 .065 .074 7.809 < 0.001 .340 .676 .443 2.255
Education - Completed secondary .811 .062 .135 13.011 < 0.001 .650 .971 .372 2.688
Education - Completed college or university 1.119 .074 .143 15.036 < 0.001 .927 1.311 .443 2.259
Income - Low (can afford food at most) -.138 .047 -.021 -2.944 .003 -.260 -.017 .777 1.287
Income - High (can afford almost everything) .004 .067 .000 0.062 .950 -.169 .177 .869 1.151
Marital Status - Single -.215 .051 -.035 -4.181 < 0.001 -.347 -.082 .566 1.767
Marital Status - Married, not living with spouse -.019 .088 -.001 -.213 .831 -.244 .207 .939 1.065
Marital Status - Divorced/Separated -.231 .136 -.011 -1.701 .089 -.581 .119 .961 1.041
Marital Status - Widowed -.423 .097 -.030 -4.376 < 0.001 -.672 -.174 .877 1.140
Marital Status - In a marriage where the husband
has more than on wife 1.460 .187 .051 7.797 < 0.001 .978 1.943 .953 1.049
Marital Status - Living with partner -.236 .212 -.007 -1.114 .265 -.782 .310 .970 1.031
4.3.2.4 Diagnostics
Table 102 - Model n. 2 diagnostics - Discussion
N. of
cases
N.
predicted
scores
Std
residuals
> |3.29|
Std
residuals
> |2.58|
Std
residuals
> |1.96|
Cook's
distance
above |1|
Durbin-
Watson
statistic
23621 18320 0.02% 0.48% 5.00% 0.00% 1.666
71
Figure 18 - Residuals and predicted values - Model n. 2 - Discussion
4.3.3 Model n. 3 – Exposure & significant interactions
4.3.3.1 Model summary
Table 103 - Model n. 3 summary - Discussion
Model R R2 Adjusted
R2
Std. Error of
the Estimate
Change Statistics
R2
Change F Change df1 df2
Sig. F
Change
1 0.174 0.030 0.030 2.778 0.030 592.956 1 18956 < 0.001
2 0.22 0.049 0.048 2.752 0.018 362.710 1 18955 < 0.001
3 0.231 0.054 0.053 2.745 0.005 20.043 5 18950 < 0.001
4 0.299 0.089 0.088 2.694 0.036 92.561 8 18942 < 0.001
5 0.38 0.144 0.143 2.611 0.055 1217.386 1 18941 < 0.001
6 0.429 0.184 0.183 2.550 0.040 155.280 6 18935 < 0.001
7 0.489 0.239 0.238 2.464 0.055 90.759 15 18920 < 0.001
72
4.3.3.2 ANOVA
Table 104 - Model n. 3 ANOVA - Discussion
Model Sum of
Squares df
Mean
Square F Sig.
1
Regression 4577.069 1 4577.069 592.956 < 0.001
Residual 146322.657 18956 7.719
Total 150899.727 18957
2
Regression 7324.427 2 3662.213 483.490 < 0.001
Residual 143575.300 18955 7.575
Total 150899.727 18957
3
Regression 8079.702 7 1154.243 153.150 < 0.001
Residual 142820.024 18950 7.537
Total 150899.727 18957
4
Regression 13452.855 15 896.857 123.599 < 0.001
Residual 137446.871 18942 7.256
Total 150899.727 18957
5
Regression 21753.418 16 1359.589 199.402 < 0.001
Residual 129146.309 18941 6.818
Total 150899.727 18957
6
Regression 27809.954 22 1264.089 194.456 < 0.001
Residual 123089.772 18935 6.501
Total 150899.727 18957
7
Regression 36072.322 37 974.928 160.638 < 0.001
Residual 114827.405 18920 6.069
Total 150899.727 18957
4.3.3.3 Coefficients
Significance testing was conducted using the parameters test and an examination of the t-statistic in
the parameter estimate tables.
Multicollinearity testing revealed that, apart from Exposure and its interactions, all variables were
acceptable, with a tolerance statistic well above 0.2 for all variables. The average Variance Inflation
Factor (VIF) is 3.283.
73
Table 105 - Model n. 3 regression coefficients - Discussion
Coefficients
t Sig.
99% Confidence
Interval for B
Collinearity
Statistics
B Std. Error Beta Lower
Bound
Upper
Bound Tolerance VIF
(Constant) 3.396 .106 31.899 < 0.001 3.121 3.670
Exposure to at least one governance
programme 1.839 .228 .257 8.054 < 0.001 1.251 2.427 .040 25.287
Sex of the respondent – Female -.456 .038 -.081 -12.018 < 0.001 -.553 -.358 .891 1.123
Age groups - 25-34 .220 .052 .035 4.222 < 0.001 .086 .354 .572 1.748
Age groups - 35-44 .343 .063 .047 5.483 < 0.001 .182 .504 .559 1.790
Age groups - 45-54 .394 .072 .045 5.494 < 0.001 .209 .578 .612 1.635
Age groups - 55-64 .318 .085 .029 3.725 < 0.001 .098 .538 .681 1.469
Age groups - 65+ .281 .099 .021 2.834 .005 .026 .537 .707 1.414
Education - Literate .254 .078 .030 3.264 .001 .054 .455 .475 2.106
Exposure for Literate -.139 .231 -.006 -0.602 .547 -.733 .455 .366 2.733
Education - Completed primary .576 .073 .084 7.938 < 0.001 .389 .763 .356 2.810
Exposure for Primary -.374 .213 -.020 -1.760 .078 -.922 .174 .312 3.204
Education - Completed secondary .923 .071 .154 12.952 < 0.001 .740 1.107 .284 3.524
Exposure for Secondary -.586 .190 -.052 -3.087 .002 -1.075 -.097 .144 6.941
Education - Completed college or university 1.199 .087 .154 13.852 < 0.001 .976 1.422 .327 3.062
Exposure for High educated -.470 .205 -.034 -2.291 .022 -.999 .059 .186 5.379
Group activity – Active members .602 .043 .106 14.015 < 0.001 .491 .713 .698 1.432
Interest in politics - Not very interested .612 .067 .092 9.065 < 0.001 .438 .786 .387 2.583
Exposure for Not very interested -1.331 .243 -.074 -5.465 < 0.001 -1.958 -.703 .220 4.544
Interest in politics - Somewhat interested 1.286 .066 .216 19.446 < 0.001 1.116 1.457 .325 3.082
Exposure for Somewhat interested -1.096 .228 -.093 -4.817 < 0.001 -1.682 -.510 .108 9.263
Interest in politics - Very interested 1.806 .072 .287 25.088 < 0.001 1.621 1.992 .308 3.246
Exposure for Very interested -1.009 .229 -.094 -4.404 < 0.001 -1.600 -.419 .089 11.272
Country - Bangladesh -1.844 .078 -.206 -23.688 < 0.001 -2.044 -1.643 .531 1.885
Country - Nepal -1.436 .068 -.191 -21.082 < 0.001 -1.612 -1.261 .490 2.039
Country - Kenya -.499 .069 -.059 -7.218 < 0.001 -.677 -.321 .604 1.657
Country - Nigeria -.571 .065 -.078 -8.784 < 0.001 -.738 -.403 .515 1.943
Country - Tanzania -.694 .068 -.093 -10.270 < 0.001 -.868 -.520 .488 2.050
Country - Myanmar -2.937 .098 -.231 -30.112 < 0.001 -3.189 -2.686 .685 1.460
Location – Urban -.013 .042 -.002 -0.303 .762 -.120 .095 .816 1.225
Income - Low (can afford food at most) -.161 .047 -.025 -3.408 .001 -.282 -.039 .771 1.297
Income - High (can afford almost everything) .011 .067 .001 0.164 .870 -.162 0.184 .869 1.151
Marital Status - Single -.209 .051 -.034 -4.074 < 0.001 -.341 -.077 .565 1.769
Marital Status - Married, not living with spouse -.015 .087 -.001 -.170 .865 -.240 .210 .939 1.065
Marital Status - Divorced/Separated -.224 .136 -.011 -1.648 .099 -.573 .126 .961 1.041
Marital Status - Widowed -.422 .096 -.030 -4.372 < 0.001 -.670 -.173 .877 1.140
Marital Status - In a marriage where the husband
has more than on wife 1.390 .190 .048 7.301 < 0.001 .899 1.880 .920 1.087
Marital Status - Living with partner -.229 .212 -.007 -1.081 .280 -.774 .316 .970 1.031
4.3.3.4 Diagnostics
Table 106 - Model n. 3 diagnostics - Discussion
N. of
cases
N.
predicted
scores
Std
residuals
> |3.29|
Std
residuals
> |2.58|
Std
residuals
> |1.96|
Cook's
distance
above |1|
Durbin-
Watson
statistic
23621 18320 0.02% 0.48% 5.04% 0.00% 1.667
74
Figure 19 - Residuals and predicted values - Model n. 3 - Discussion
4.3.4 Model n. 4 – Exposure & Country interactions
4.3.4.1 Model summary
Table 107 - Model n. 4 summary - Discussion
Model R R2 Adjusted
R2
Std. Error of
the Estimate
Change Statistics
R2
Change F Change df1 df2
Sig. F
Change
1 0.174 0.030 0.030 2.778 0.030 592.956 1 18956 < 0.001
2 0.377 0.142 0.141 2.614 0.112 205.419 12 18944 < 0.001
3 0.462 0.214 0.213 2.503 0.072 432.609 4 18940 < 0.001
4 0.49 0.240 0.239 2.462 0.026 34.312 19 18921 < 0.001
75
4.3.4.2 ANOVA
Table 108 - Model n. 4 ANOVA - Discussion
Model Sum of
Squares df
Mean
Square F Sig.
1
Regression 4577.069 1 4577.069 592.956 < 0.001
Residual 146322.657 18956 7.719
Total 150899.727 18957
2
Regression 21424.612 13 1648.047 241.132 < 0.001
Residual 129475.114 18944 6.835
Total 150899.727 18957
3
Regression 32263.687 17 1897.864 302.990 < 0.001
Residual 118636.040 18940 6.264
Total 150899.727 18957
4
Regression 36215.122 36 1005.976 165.969 < 0.001
Residual 114684.605 18921 6.061
Total 150899.727 18957
4.3.4.3 Coefficients
Significance testing was conducted using the parameters test and an examination of the t-statistic in
the parameter estimate tables.
Multicollinearity testing revealed that Exposure is the only variable with Tolerance level below 0.2,
which is due to its interactions with the country categories. The average Variance Inflation Factor
(VIF) is 1.934.
76
Table 109 - Model n. 4 regression coefficients - Discussion
Coefficients
t Sig.
99% Confidence
Interval for B
Collinearity
Statistics
B Std. Error Beta Lower
Bound
Upper
Bound Tolerance VIF
(Constant) 3.763 .104 36.226 < 0.001 3.495 4.030
Exposure to at least one governance
programme .054 .108 .008 0.502 .616 -.223 .331 .178 5.625
Country - Bangladesh -2.003 .085 -.224 -23.450 < 0.001 -2.223 -1.783 .440 2.272
Exposure for Bangladesh .380 .225 .013 1.688 .091 -.200 .961 .652 1.533
Country - Nepal -1.758 .081 -.234 -21.781 < 0.001 -1.966 -1.550 .349 2.866
Exposure for Nepal 1.130 .158 .079 7.147 < 0.001 .722 1.537 .328 3.052
Country - Kenya -.647 .077 -.076 -8.438 < 0.001 -.845 -.450 .489 2.043
Exposure for Kenya .824 .220 .029 3.745 < 0.001 .257 1.391 .651 1.536
Country - Nigeria -.589 .078 -.080 -7.567 < 0.001 -.790 -.389 .358 2.792
Exposure for Nigeria .115 .151 .009 0.760 .447 -.275 .505 .292 3.425
Country - Tanzania -.854 .075 -.115 -11.352 < 0.001 -1.048 -.661 .392 2.549
Exposure for Tanzania .448 .189 .020 2.366 .018 -.040 .935 .564 1.772
Country - Myanmar -3.145 .104 -.247 -30.317 < 0.001 -3.413 -2.878 .605 1.654
Exposure for Myanmar .940 .370 .018 2.539 .011 -.014 1.893 .844 1.184
Group activity – Active members .596 .043 .105 13.872 < 0.001 .485 .706 .698 1.433
Interest in politics - Not very interested .460 .061 .069 7.558 < 0.001 .303 .617 .475 2.104
Interest in politics - Somewhat interested 1.179 .059 .198 20.062 < 0.001 1.027 1.330 .411 2.434
Interest in politics - Very interested 1.708 .063 .271 27.143 < 0.001 1.546 1.870 .403 2.482
Sex of the respondent – Female -.445 .038 -.079 -11.737 < 0.001 -.543 -.348 .888 1.126
Location – Urban -.043 .042 -.007 -1.040 .299 -.151 .064 .813 1.230
Age groups - 25-34 .223 .052 .036 4.293 < 0.001 .089 .357 .573 1.744
Age groups - 35-44 .330 .062 .045 5.279 < 0.001 .169 .491 .560 1.784
Age groups - 45-54 .388 .071 .044 5.426 < 0.001 .204 .572 .614 1.628
Age groups - 55-64 .312 .085 .028 3.664 < 0.001 .093 .532 .682 1.465
Age groups - 65+ .273 .099 .021 2.760 .006 .018 .528 .711 1.406
Education - Literate .218 .069 .026 3.152 .002 .040 .396 .602 1.661
Education - Completed primary .475 .065 .070 7.298 < 0.001 .308 .643 .441 2.270
Education - Completed secondary .772 .063 .129 12.349 < 0.001 .611 .933 .368 2.715
Education - Completed college or university 1.073 .075 .138 14.362 < 0.001 .881 1.265 .438 2.285
Income - Low (can afford food at most) -.147 .047 -.023 -3.132 .002 -.268 -.026 .775 1.291
Income - High (can afford almost everything) -.014 .067 -.001 -0.209 .835 -.187 .159 .868 1.152
Marital Status - Single -.219 .051 -.036 -4.266 < 0.001 -.351 -0.087 .565 1.769
Marital Status - Married, not living with spouse -.021 .087 -.002 -0.238 .812 -.246 0.204 .939 1.065
Marital Status - Divorced/Separated -.243 .136 -.012 -1.792 .073 -.592 .106 .961 1.041
Marital Status - Widowed -.417 .096 -.029 -4.329 < 0.001 -.666 -.169 .877 1.141
Marital Status - In a marriage where the husband
has more than on wife 1.541 .188 .054 8.188 < 0.001 1.056 2.026 .940 1.064
Marital Status - Living with partner -.245 .212 -.007 -1.157 .247 -.790 .300 .970 1.031
4.3.4.4 Diagnostics
Table 110 - Model n. 4 diagnostics - Discussion
N. of
cases
N.
predicted
scores
Std
residuals
> |3.29|
Std
residuals
> |2.58|
Std
residuals
> |1.96|
Cook's
distance
above |1|
Durbin-
Watson
statistic
23621 18320 0.02% 0.44% 5.05% 0.00% 1.669
77
Figure 20 - Residuals and predicted values - Model n. 4 - Discussion
78
4.4 Regression models – Efficacy
4.4.1 Model n. 1 – Exposure with all confounders
4.4.1.1 Model summary
The model includes 23621 observations. Missing data were handled using pair wise deletion. 18320
cases have no missing data.
Table 111 - Model n. 1 summary - Efficacy
Model R R2 Adjusted
R2
Std. Error of
the Estimate
Change Statistics
R2
Change F Change df1 df2
Sig. F
Change
1 0.011 0.000 0.000 1.904 0.000 2.459 1 18956 0.117
2 0.174 0.030 0.030 1.875 0.030 147.891 4 18952 < 0.001
3 0.331 0.110 0.108 1.798 0.079 67.432 25 18927 < 0.001
4.4.1.2 ANOVA
Table 112 - Model n. 1 ANOVA - Efficacy
Model Sum of
Squares df
Mean
Square F Sig.
1
Regression 8.913 1 8.913 2.459 0.117
Residual 68697.039 18956 3.624
Total 68705.952 18957
2
Regression 2088.300 5 417.660 118.820 < 0.001
Residual 66617.652 18952 3.515
Total 68705.952 18957
3
Regression 7536.543 30 251.218 77.732 < 0.001
Residual 61169.409 18927 3.232
Total 68705.952 18957
4.4.1.3 Coefficients
Significance testing was conducted using the parameters test and an examination of the t-statistic in
the parameter estimate tables.
Multicollinearity testing was conducted and all variables were acceptable, with a tolerance statistic
well above 0.2 for all variables and an average Variance Inflation Factor (VIF) of 1.643.
79
Table 113 - Model n. 1 regression coefficients - Efficacy
Coefficients
t Sig.
99% Confidence
Interval for B
Collinearity
Statistics
B Std. Error Beta Lower
Bound
Upper
Bound Tolerance VIF
(Constant) 4.441 .073 61.152 < 0.001 4.254 4.628
Exposure to at least one governance
programme .097 .036 .020 2.713 .007 .005 .188 .865 1.156
Sex of the respondent – Female -.025 .028 -.007 -0.898 .369 -.096 .046 .892 1.121
Group activity – Active members .299 .031 .078 9.539 < 0.001 .218 .379 .699 1.430
Interest in politics - Not very interested .140 .044 .031 3.146 .002 .025 .254 .478 2.094
Interest in politics - Somewhat interested .564 .043 .141 13.205 < 0.001 .454 .674 .414 2.414
Interest in politics - Very interested 0.813 .046 .191 17.737 < 0.001 0.695 0.931 .405 2.471
Country - Bangladesh 1.468 .057 .243 25.917 < 0.001 1.322 1.614 .534 1.874
Country - Nepal 0.343 .050 .068 6.921 < 0.001 0.215 0.471 .493 2.029
Country - Kenya .549 .050 .096 10.896 < 0.001 .419 .679 .605 1.653
Country - Nigeria -.271 .047 -.055 -5.720 < 0.001 -0.393 -.149 .516 1.936
Country - Tanzania .239 .049 .048 4.875 < 0.001 0.113 .366 .492 2.031
Country - Myanmar 1.645 .071 .191 23.189 < 0.001 1.462 1.827 .690 1.450
Location – Urban -.140 .030 -.035 -4.614 < 0.001 -.218 -.062 .819 1.221
Age groups - 25-34 -.002 .038 -.001 -0.063 .950 -.100 .095 .573 1.744
Age groups - 35-44 .022 .046 .004 0.488 .625 -.095 .140 .561 1.783
Age groups - 45-54 .057 .052 .010 1.097 .273 -.077 .192 .614 1.628
Age groups - 55-64 .078 .062 .010 1.258 .208 -.082 0.239 .683 1.465
Age groups - 65+ .187 .072 .021 2.592 .010 .001 0.373 .711 1.406
Education - Literate -.106 .050 -.019 -2.098 .036 -.236 .024 .604 1.655
Education - Completed primary .070 .047 .015 1.470 .141 -.052 .192 .443 2.255
Education - Completed secondary .054 .045 .013 1.194 .232 -.063 .171 .372 2.687
Education - Completed college or university -.103 .054 -.020 -1.893 .058 -.242 .037 .443 2.259
Income - Low (can afford food at most) .121 .034 .027 3.530 < 0.001 .033 .209 .777 1.287
Income - High (can afford almost everything) .106 .049 .016 2.158 .031 -.020 .232 .869 1.151
Marital Status - Single -.009 .037 -.002 -0.242 .809 -.105 .087 .566 1.767
Marital Status - Married, not living with spouse -.261 .064 -.029 -4.083 < 0.001 -.425 -.096 .939 1.065
Marital Status - Divorced/Separated .072 .099 .005 0.729 .466 -.183 .327 .961 1.040
Marital Status - Widowed -.086 .070 -.009 -1.228 .219 -.268 .095 .877 1.140
Marital Status - In a marriage where the husband
has more than on wife -.101 .136 -.005 -0.738 .460 -.452 0.251 .953 1.049
Marital Status - Living with partner -.027 .154 -.001 -.175 .861 -.425 .371 .970 1.031
4.4.1.4 Diagnostics
Table 114 - Model n. 1 diagnostics - Efficacy
N. of
cases
N.
predicted
scores
Std
residuals
> |3.29|
Std
residuals
> |2.58|
Std
residuals
> |1.96|
Cook's
distance
above |1|
Durbin-
Watson
statistic
23621 18320 0.12% 1.15% 5.79% 0.00% 1.614
80
Figure 21 - Residuals and predicted values - Model n. 1 - Efficacy
4.4.2 Model n. 2 – Exposure & Gender interaction
4.4.2.1 Model summary
Table 115 - Model n. 2 summary - Efficacy
Model R R2 Adjusted
R2
Std. Error of
the Estimate
Change Statistics
R2
Change F Change df1 df2
Sig. F
Change
1 0.011 0.000 0.000 1.904 0.000 2.459 1 18956 0.117
2 0.035 0.001 0.001 1.903 0.001 10.336 2 18954 < 0.001
3 0.175 0.030 0.030 1.875 0.029 143.073 4 18950 < 0.001
4 0.331 0.110 0.108 1.798 0.079 70.199 24 18926 < 0.001
81
4.4.2.2 ANOVA
Table 116 - Model n. 2 ANOVA - Efficacy
Model Sum of
Squares df
Mean
Square F Sig.
1
Regression 8.913 1 8.913 2.459 0.117
Residual 68697.039 18956 3.624
Total 68705.952 18957
2
Regression 83.752 3 27.917 7.711 < 0.001
Residual 68622.200 18954 3.62
Total 68705.952 18957
3
Regression 2095.399 7 299.343 85.160 < 0.001
Residual 66610.553 18950 3.515
Total 68705.952 18957
4
Regression 7540.330 31 243.236 75.263 < 0.001
Residual 61165.622 18926 3.232
Total 68705.952 18957
4.4.2.3 Coefficients
Significance testing was conducted using the parameters test and an examination of the t-statistic in
the parameter estimate tables.
Multicollinearity testing was conducted and all variables were acceptable, with a tolerance statistic
well above 0.2 for all variables and an average Variance Inflation Factor (VIF) of 1.682.
82
Table 117 - Model n. 2 regression coefficients - Efficacy
Coefficients
t Sig.
99% Confidence
Interval for B
Collinearity
Statistics
B Std. Error Beta Lower
Bound
Upper
Bound Tolerance VIF
(Constant) 4.448 .073 61.030 < 0.001 4.260 4.636
Exposure to at least one governance
programme .066 .045 .014 1.470 .141 -.050 .183 .537 1.862
Sex of the respondent – Female -.039 .031 -.010 -1.273 .203 -.118 .040 .731 1.368
Exposure*Sex - Exposure for women .078 .072 .010 1.082 .279 -.107 .262 .536 1.865
Group activity – Active members .299 .031 .078 9.547 < 0.001 .218 .380 .699 1.431
Interest in politics - Not very interested .138 .044 .031 3.110 .002 .024 .252 .477 2.096
Interest in politics - Somewhat interested .562 .043 .140 13.148 < 0.001 .452 .672 .413 2.419
Interest in politics - Very interested 0.812 .046 .191 17.720 < 0.001 0.694 0.931 .405 2.472
Country - Bangladesh 1.470 .057 .244 25.939 < 0.001 1.324 1.616 .533 1.877
Country - Nepal 0.346 .050 .068 6.969 < 0.001 0.218 0.474 .492 2.035
Country - Kenya .549 .050 .096 10.900 < 0.001 .419 .679 .605 1.653
Country - Nigeria -.272 .047 -.055 -5.737 < 0.001 -0.394 -.150 .516 1.937
Country - Tanzania .239 .049 .048 4.872 < 0.001 0.113 .365 .492 2.031
Country - Myanmar 1.645 .071 .192 23.195 < 0.001 1.462 1.828 .690 1.450
Location – Urban -.140 .030 -.035 -4.604 < 0.001 -.218 -.062 .819 1.221
Age groups - 25-34 -.002 .038 .000 -0.050 .960 -.100 .096 .573 1.744
Age groups - 35-44 .023 .046 .005 0.514 .607 -.094 .141 .560 1.784
Age groups - 45-54 .059 .052 .010 1.125 .261 -.076 .193 .614 1.629
Age groups - 55-64 .079 .062 .011 1.272 .203 -.081 0.240 .683 1.465
Age groups - 65+ .187 .072 .021 2.586 .010 .001 0.373 .711 1.406
Education - Literate -.105 .050 -.018 -2.084 .037 -.235 .025 .604 1.655
Education - Completed primary .070 .047 .015 1.485 .137 -.052 .193 .443 2.255
Education - Completed secondary .055 .045 .014 1.212 .225 -.062 .172 .372 2.688
Education - Completed college or university -.102 .054 -.019 -1.879 .060 -.242 .038 .443 2.259
Income - Low (can afford food at most) .122 .034 .028 3.547 < 0.001 .033 .210 .777 1.287
Income - High (can afford almost everything) .106 .049 .016 2.158 .031 -.020 .232 .869 1.151
Marital Status - Single -.009 .037 -.002 -0.242 .809 -.105 .087 .566 1.767
Marital Status - Married, not living with spouse -.262 .064 -.029 -4.098 < 0.001 -.426 -.097 .939 1.065
Marital Status - Divorced/Separated .074 .099 .005 0.744 .457 -.181 .329 .961 1.041
Marital Status - Widowed -.085 .070 -.009 -1.210 .226 -.267 .096 .877 1.140
Marital Status - In a marriage where the husband
has more than on wife -.099 .136 -.005 -0.724 .469 -.450 0.253 .953 1.049
Marital Status - Living with partner -.024 .154 -.001 -.158 .875 -.422 .374 .970 1.031
4.4.2.4 Diagnostics
Table 118 - Model n. 2 diagnostics - Efficacy
N. of
cases
N.
predicted
scores
Std
residuals
> |3.29|
Std
residuals
> |2.58|
Std
residuals
> |1.96|
Cook's
distance
above |1|
Durbin-
Watson
statistic
23621 18320 0.12% 1.14% 5.79% 0.00% 1.614
83
Figure 22 - Residuals and predicted values - Model n. 2 - Efficacy
4.4.3 Model n. 3 – Exposure & significant interactions
4.4.3.1 Model summary
Table 119 - Model n. 3 summary - Efficacy
Model R R2 Adjusted
R2
Std. Error of
the Estimate
Change Statistics
R2
Change F Change df1 df2
Sig. F
Change
1 0.011 0.000 0.000 1.904 0.000 2.459 1 18956 0.117
2 0.172 0.030 0.029 1.876 0.029 95.867 6 18950 < 0.001
3 0.186 0.035 0.034 1.871 0.005 9.671 10 18940 < 0.001
4 0.19 0.036 0.035 1.870 0.002 7.625 4 18936 < 0.001
5 0.335 0.112 0.111 1.795 0.076 85.615 19 18917 < 0.001
84
4.4.3.2 ANOVA
Table 120 - Model n. 3 ANOVA - Efficacy
Model Sum of
Squares df
Mean
Square F Sig.
1
Regression 8.913 1 8.913 2.459 0.117
Residual 68697.039 18956 3.624
Total 68705.952 18957
2
Regression 2032.693 7 290.385 82.534 < 0.001
Residual 66673.259 18950 3.518
Total 68705.952 18957
3
Regression 2371.390 17 139.494 39.829 < 0.001
Residual 66334.562 18940 3.502
Total 68705.952 18957
4
Regression 2478.059 21 118.003 33.740 < 0.001
Residual 66227.893 18936 3.497
Total 68705.952 18957
5
Regression 7722.103 40 193.053 59.884 < 0.001
Residual 60983.849 18917 3.224
Total 68705.952 18957
4.4.3.3 Coefficients
Significance testing was conducted using the parameters test and an examination of the t-statistic in
the parameter estimate tables.
Multicollinearity testing revealed that, apart from Exposure and its interactions, all variables were
acceptable, with a tolerance statistic well above 0.2 for all variables. The average Variance Inflation
Factor (VIF) is 2.770.
85
Table 121 - Model n. 3 regression coefficients - Efficacy
Coefficients
t Sig.
99% Confidence
Interval for B
Collinearity
Statistics
B Std. Error Beta Lower
Bound
Upper
Bound Tolerance VIF
(Constant) 4.288 .077 55.815 < 0.001 4.090 4.486
Exposure to at least one governance
programme .965 .149 .200 6.456 < 0.001 .580 1.350 .049 20.404
Sex of the respondent – Female -.021 .028 -.005 -0.745 .456 -.092 .051 .891 1.123
Age groups - 25-34 .061 .043 .015 1.422 .155 -.049 .171 .450 2.224
Exposure for 25-34 -.298 .095 -.035 -3.138 .002 -.543 -.053 .379 2.636
Age groups - 35-44 .091 .051 .018 1.779 .075 -.041 .222 .448 2.232
Exposure for 35-44 -.290 .110 -.027 -2.648 .008 -.573 -.008 .466 2.146
Age groups - 45-54 .146 .059 .024 2.475 .013 -.006 .297 .482 2.073
Exposure for 45-54 -.390 .125 -.030 -3.121 .002 -.712 -.068 .523 1.912
Age groups - 55-64 .142 .069 .019 2.047 .041 -.037 .320 .551 1.816
Exposure for 55-64 -.254 .159 -.014 -1.595 .111 -.663 .156 .641 1.560
Age groups - 65+ .301 .079 .034 3.832 < 0.001 .099 .504 .599 1.670
Exposure for 65 or more -.619 .207 -.024 -2.995 .003 -1.151 -.087 .743 1.346
Education - Literate -.091 .051 -.016 -1.798 .072 -.221 .039 .600 1.668
Education - Completed primary .091 .048 .020 1.901 .057 -.032 .213 .438 2.281
Education - Completed secondary .075 .046 .018 1.633 .102 -.043 .192 .368 2.720
Education - Completed college or university -.088 .054 -.017 -1.622 .105 -.228 .052 .439 2.276
Group activity – Active members .292 .031 .076 9.308 < 0.001 .211 .372 .698 1.433
Interest in politics - Not very interested .246 .049 .055 4.993 < 0.001 .119 .372 .388 2.580
Exposure for Not very interested -.907 .177 -.075 -5.130 < 0.001 -1.363 -.452 .222 4.513
Interest in politics - Somewhat interested .666 .048 .166 13.842 < 0.001 .542 .789 .326 3.066
Exposure for Somewhat interested -.813 .164 -.102 -4.947 < 0.001 -1.236 -.389 .110 9.087
Interest in politics - Very interested .904 .052 .213 17.313 < 0.001 .769 1.038 .311 3.213
Exposure for Very interested -.745 .166 -.103 -4.499 < 0.001 -1.172 -.318 .090 11.082
Country - Bangladesh 1.471 .057 .244 25.961 < 0.001 1.325 1.617 .532 1.881
Country - Nepal .338 .050 .067 6.826 < 0.001 .211 .466 .492 2.033
Country - Kenya .550 .050 .096 10.914 < 0.001 .420 .680 .604 1.657
Country - Nigeria -.275 .048 -.055 -5.783 < 0.001 -.397 -.152 .512 1.954
Country - Tanzania .252 .049 .050 5.126 < 0.001 .125 .379 .489 2.045
Country - Myanmar 1.653 .071 .192 23.223 < 0.001 1.469 1.836 .683 1.463
Location – Urban -.130 .030 -.033 -4.288 < 0.001 -.209 -.052 .815 1.226
Income - Low (can afford food at most) .062 .038 .014 1.638 .101 -.035 .158 .645 1.551
Exposure for Low income .239 .090 .023 2.642 .008 .006 .471 .615 1.625
Income - High (can afford almost everything) .086 .057 .013 1.524 .128 -.060 .233 .645 1.550
Exposure for High income .105 .112 .008 0.937 .349 -.184 .394 .612 1.633
Marital Status - Single .008 .038 .002 0.216 .829 -.089 .105 .562 1.780
Marital Status - Married, not living with spouse -.260 .064 -.029 -4.077 < 0.001 -.424 -.096 .938 1.066
Marital Status - Divorced/Separated .069 .099 .005 0.694 .488 -.186 .323 .960 1.041
Marital Status - Widowed -.096 .070 -.010 -1.360 .174 -.277 .086 .874 1.144
Marital Status - In a marriage where the husband
has more than on wife -.125 .137 -.006 -0.912 .362 -.479 0.229 .938 1.066
Marital Status - Living with partner -.043 .154 -.002 -.277 .782 -.440 .355 .969 1.032
4.4.3.4 Diagnostics
Table 122 - Model n. 3 diagnostics - Efficacy
N. of
cases
N.
predicted
scores
Std
residuals
> |3.29|
Std
residuals
> |2.58|
Std
residuals
> |1.96|
Cook's
distance
above |1|
Durbin-
Watson
statistic
23621 18320 0.07% 1.15% 5.75% 0.00% 1.615
86
Figure 23 - Residuals and predicted values - Model n. 3 - Efficacy
4.4.4 Model n. 4 – Exposure & Country interactions
4.4.4.1 Model summary
Table 123 - Model n. 4 summary - Efficacy
Model R R2 Adjusted
R2
Std. Error of
the Estimate
Change Statistics
R2
Change F Change df1 df2
Sig. F
Change
1 0.011 0.000 0.000 1.904 0.000 2.459 1 18956 0.117
2 0.28 0.078 0.078 1.828 0.078 133.768 12 18944 < 0.001
3 0.328 0.108 0.107 1.799 0.030 157.321 4 18940 < 0.001
4 0.336 0.113 0.111 1.795 0.005 5.410 19 18921 < 0.001
87
4.4.4.2 ANOVA
Table 124 - Model n. 4 ANOVA - Efficacy
Model Sum of
Squares df
Mean
Square F Sig.
1
Regression 8.913 1 8.913 2.459 0.117
Residual 68697.039 18956 3.624
Total 68705.952 18957
2
Regression 5375.224 13 413.479 123.683 < 0.001
Residual 63330.728 18944 3.343
Total 68705.952 18957
3
Regression 7411.728 17 435.984 134.720 < 0.001
Residual 61294.224 18940 3.236
Total 68705.952 18957
4
Regression 7742.911 36 215.081 66.754 < 0.001
Residual 60963.041 18921 3.222
Total 68705.952 18957
4.4.4.3 Coefficients
Significance testing was conducted using the parameters test and an examination of the t-statistic in
the parameter estimate tables.
Multicollinearity testing revealed that Exposure is the only variable with Tolerance level below 0.2,
which is due to its interactions with the country categories. The average Variance Inflation Factor
(VIF) is 1.934.
88
Table 125 - Model n. 4 regression coefficients - Efficacy
Coefficients
t Sig.
99% Confidence
Interval for B
Collinearity
Statistics
B Std. Error Beta Lower
Bound
Upper
Bound Tolerance VIF
(Constant) 4.295 .076 56.718 < 0.001 4.100 4.490
Exposure to at least one governance
programme .543 .078 .112 6.918 < 0.001 .341 .745 .178 5.625
Country - Bangladesh 1.639 .062 .272 26.321 < 0.001 1.478 1.799 .440 2.272
Exposure for Bangladesh -.835 .164 -.043 -5.083 < 0.001 -1.258 -.412 .652 1.533
Country - Nepal .564 .059 .111 9.578 < 0.001 .412 .715 .349 2.866
Exposure for Nepal -.796 .115 -.083 -6.904 < 0.001 -1.092 -.499 .328 3.052
Country - Kenya .680 .056 .119 12.152 < 0.001 .536 .824 .489 2.043
Exposure for Kenya -.611 .160 -.032 -3.806 < 0.001 -1.024 -.197 .651 1.536
Country - Nigeria -.189 .057 -.038 -3.330 .001 -.335 -.043 .358 2.792
Exposure for Nigeria -.359 .110 -.041 -3.249 .001 -.643 -.074 .292 3.425
Country - Tanzania .387 .055 .077 7.060 < 0.001 .246 .529 .392 2.549
Exposure for Tanzania -.628 .138 -.042 -4.556 < 0.001 -.984 -.273 .564 1.772
Country - Myanmar 1.812 .076 .211 23.950 < 0.001 1.617 2.006 .605 1.654
Exposure for Myanmar -.997 .270 -.028 -3.695 < 0.001 -1.692 -.302 .844 1.184
Group activity – Active members .307 .031 .081 9.820 < 0.001 .227 .388 .698 1.433
Interest in politics - Not very interested .143 .044 .032 3.231 .001 .029 .258 .475 2.104
Interest in politics - Somewhat interested .554 .043 .138 12.928 < 0.001 .443 .664 .411 2.434
Interest in politics - Very interested .807 .046 .190 17.591 < 0.001 .689 .925 .403 2.482
Sex of the respondent – Female -.038 .028 -.010 -1.377 .168 -.109 .033 .888 1.126
Location – Urban -.128 .030 -.032 -4.202 < 0.001 -.206 -.049 .813 1.230
Age groups - 25-34 -.004 .038 -.001 -0.103 .918 -.102 .094 .573 1.744
Age groups - 35-44 .026 .046 .005 0.568 .570 -.091 .143 .560 1.784
Age groups - 45-54 .058 .052 .010 1.113 .266 -.076 .192 .614 1.628
Age groups - 55-64 .076 .062 .010 1.215 .225 -.085 .236 .682 1.465
Age groups - 65+ .182 .072 .021 2.524 .012 -.004 .368 .711 1.406
Education - Literate -.103 .050 -.018 -2.048 .041 -.233 .027 .602 1.661
Education - Completed primary .087 .047 .019 1.830 .067 -.035 .209 .441 2.270
Education - Completed secondary .073 .046 .018 1.607 .108 -.044 .191 .368 2.715
Education - Completed college or university -.078 .054 -.015 -1.437 .151 -.219 .062 .438 2.285
Income - Low (can afford food at most) .128 .034 .029 3.729 < 0.001 .040 .216 .775 1.291
Income - High (can afford almost everything) .114 .049 .017 2.336 .019 -.012 .240 .868 1.152
Marital Status - Single -.003 .037 -.001 -0.076 .939 -.099 0.093 .565 1.769
Marital Status - Married, not living with spouse -.258 .064 -.029 -4.045 < 0.001 -.422 -0.094 .939 1.065
Marital Status - Divorced/Separated .080 .099 .006 0.804 .421 -.175 .334 .961 1.041
Marital Status - Widowed -.090 .070 -.009 -1.274 .203 -.271 .092 .877 1.141
Marital Status - In a marriage where the husband
has more than on wife -.195 .137 -.010 -1.424 .155 -.549 .158 .940 1.064
Marital Status - Living with partner -.030 .154 -.001 -.191 .848 -.427 .368 .970 1.031
4.4.4.4 Diagnostics
Table 126 - Model n. 4 diagnostics - Efficacy
N. of
cases
N.
predicted
scores
Std
residuals
> |3.29|
Std
residuals
> |2.58|
Std
residuals
> |1.96|
Cook's
distance
above |1|
Durbin-
Watson
statistic
23621 18320 0.14% 1.14% 5.88% 0.00% 1.617
89
Figure 24 - Residuals and predicted values - Model n. 4 - Efficacy