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Before-and-after design
Have a pretest and posttest but nocomparison group,subjects exposed to
treatment serve at an earlier time as their owncontrols
Absence of a comparison/control group
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Validity in experiments
Internal validity-causalGeneralizability-able to apply the findings to some
clearly defined larger population
Cross-population generalizability-generalize acrosssubgroups and to oher populations and settings
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Unrepresentative sample
Some characteristics are
overrepresented orunderrepresented
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Types of experimental designs
Experimental design
Quasi-experimental designNonexperimental design
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Two types of before-and afterdesigns
1.Time series designs-consisting of manypretests and posttest observations of same
group(30 or more) 2. repeated measure paneldesign-several pretests and post test of samegroup
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Two major types of quasi-experimental designs
1. Nonequivalent control group
design 2. Before-and-after design
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Two major types of quasi-experimental designs
1. Nonequivalent control group designs-norandom assignment to groups 2. before and
after design- has pretest and posttest nocomparison group
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Two functions of Probes
1. They motivate the respondent to elaborateor clarify an answer or to explain reasons 2.
they help focus the conversation on thespecific topic of the interview
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True Experiments must haveat least 3 things
1. An experimental and control group 2.variation in the independent variable before
assessment of change in the dependentvariable(treatment) 3. random assignment totwo groups
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Time Series Design
Research designs in which pretests and posttests areare available on a number of occassions before and
after the introduction of independent variable at least 3
sets of measures before and afterO1 O2 O3 X O4 O5 O6
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The Principles of Interviewing
1. Respondents need to feel that their interaction withthe interviewer will be pleasant and satisfying 2. the
respondents need to see the study as being worthwhile
3. barriers to he interview in the respondents mindneed to be overcome-misperceptions and suspicion ofrespondent adddressed
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The Personal Interview
Regarded as a face-to-face interpersonal rolesituation in which an interviewer asks
respondents questions to obtains answersrelated to research hypothesis
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The Classic ExperimentalDesign
Experimental group, control group
randomization pretest posttest
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Telephone survey
Or telephone interview
A semipersonal method of collectinginformation,convenient and cost saving
method
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Telephone survey
Random digit dialing-draw a random sample of telephonenumbers, requires the identification of all working telephoneexchanges in the target area.a potential telephone number is
created by randomly selecting an exchange and thenappending a random number between 0001 and
9999.Additional numbers are created by repeating these twosteps.Nonresidential and nonworking numbers are excluded
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Target population
A set of elements larger than ordifferent from the population sampled
and to which the researcher would liketo generalize study findings.
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Systematic sampling
Select every kth element in a population,where k isdetermined by dividing the population sixe by the
desired sample size. Select a random number between
0 and k and picking that element in thepopulation,systematically pick every kth element
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Survey Sampling
Sampling designed to produce
information about particular
characteristics of a finite population.
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Survey research methods
Provide ways to describe the variablesin populations and to test the
relationships among variables inpopulations.
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Survey research is popularbecause of 3 features
1. versatility-cover a range of topics,computertechnology has made surveys more versatile 2.
efficiency-many variables can be measured without
greatly increasing the time or cost 3.generalizability-lend themselves to probability sampling from largepopulations.
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Survey Research Center U ofMich pointers
1. Tell respondent who you are and whom yourepresent 2. Tell what you are doing to stimulate
interest 3. tell how he or she was chosen 4. adapt
approach to situation5. try to create relatioship ofconfidence and understanding-rapport 5. initialinstructions should be brief
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Survey Research
Involves the collection of information
from a sample of individuals through
their response to questions.
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Stratified samples
Done by dividing the population intogroups(strata) that are homogeneous
on one or more traits,then samplingfrom each of these groups
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Stratified Proportionatesample
The number of elements selected from each stratum isproportional to that stratums representation in the
population
The same number of sampling units from each stratumor a uniform sampling fraction (n/N)
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Stratified Disproportionatesample
Chosen to yield numbers in a stratum to allow intensiveanalysis of that particular stratum
Variable sampling fractions,total number in each
stratum is different,population parameters have to beweighted by the number of each stratum
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Standard error
Allows the researcher to determine the probability thata given sample estimate is close to the actual
population value.
S.E.=standard error,the distribution of all samplesabout the mean of the samples is S.E.Calculate
standard deviation and estimate the S. E.
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Simple random sampling
Numbering all population elements,thenselecting enough random numbers to
complete a sample of the desired size.It issimple but inconvenient with largepopulations
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Sampling Theory
Major objective is to provide accurateestimates of unknown parameters in
population from sample statisticsPopulation=parameter sample=statistic
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Sampling Error -contd
The larger the sampling error,the
less representative the sample.
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Sampling Error
Any difference between the
characteristics of a sample andthe characteristics of a population
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Sampling distribution
When an infinite number of independentlyselected sample values such as the meansare placed in a distribution,the distribution is
called the sampling distributionIts standard deviation is the standard error
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Sample generalizability
Refers to the ability to generalize from
a sample ,or subset of a larger
population to that population itself.
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Sample
A subset of a population that is used to
study the population as a whole.
Subset=sample
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Research designs are
Cross-sectional design a study in which dataare collected at only one point in time or
longitudinal design-research in which data arecollected at two or more points in time,datacan be ordered in time
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Research Design
Is a blueprint for research
A plan for collecting,analyzing and interpreting datathat allows the investigator to make causal inferences
Process for deciding what aspects well observe,ofwhom,for what purpose
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Representative sample
A sample that looks like thepopulation from which it was selected
in all respects that are potentiallyrelevant to the study.
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Random selection procedures
Ensure that every sampling unit of thepopulation has an equal and known
probability of being included in the sample,theprobability is n/N n=sample, N=population
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Random Selection
Each element has an equal chance of
selection independent of any other
event in the selection process
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Quasi-experimental design
Comparison group comparable toexperimental group in critical ways
Subjects are not randomly assigned tothe groups
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Quasi-experimental design
Subjects are not randomly
assigned to to the experimentaland control or comparison group
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Quasi experiments differ fromexperiments in their lack of
Randomization is a defining characteristic ofexperiments
In time series designs the moremeasurements of the dependent variable youet, the stronger your design
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Purposive or judgmentalsample
Select a sample that, in their
subjective judgment,isrepresentative of the population
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Procedures of Control
1. Randomization or random assignment-removes bias fromthe assignment process by relying on chance-flipping coin or
random number table assures that case has an equalprobability of being assigned to either group 2. matching- or
pairwise matching,for each case in experimental group,another one with identical characteristics is selected for the
control group
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Probing
The technique used by the
interviewer to stimulate discussionand obtain more information
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Probability vs. NonprobabilitySampling
Probability sample allows estimates topopulation from sample Nonprobability
sample-list of sample population isunavailable-e;g, illegal residents, drug addicts
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Probability Sample Designs
1. random sample 2. systematicsamples 3. stratified samples-
proportionate, disproportionate 4.cluster samples 5. multistage samples
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pretests
Measures the dependent variables prior tothe experimental intervention,they provide a
direct measure of how much the experimentaland comparison groups changed overtime,tests effects of intervention
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PPS-probability proportionateto size
Type of multistage cluster sample inwhich clusters are selected,not with
equal probabilities(EPSEM) but withprobabilities proportionate to their sizes
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posttest
Measurement of the outcome in
both groups after the experimentalgroup has received the treatment
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Post test Only Control GroupDesign
Posttest
R X 01
R 02
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Population-finite or infinite
Finite population-contains a countablenumber of sampling units
Infinite population-consists of an endlessnumber of sampling units,an unlimited
number of coin tosses
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Population
The entire set of individuals or otherentities to which study findings are to
be generalizedWhole=population
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Omnibus survey
A survey that covers a range of topics ofinterest to different social scientists,example
General Social Survey GSS of the NationalOpinion Research Center at the University ofChicago
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Nonschedule-structuredInterview
Focused and structured but the respondentsare given much liberty in expressing their
definition of a situation that is presented tothem.Permits the researcher to obtain detailsof personal reactions,specific emotions, etc
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Nonscheduled Interview
Least structured form,or nondirective.Noprespecified set ofquestions is used,nor are the questions asked in a specific
order.No schedule is used. With little or no directon from theinteriewer, respondents are encouraged to relate their
experiences,to reveal opinion and attitude as they see fit.Interviewer has freedom to probe and raise questions
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Nonprobability SampleDesigns
1. Convenience samples 2. purposiveor judgmental samples 3. snowball
samples 4.quota samples
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Nonexperimental designs
1. Ex post facto(after the fact) controlgroup design-comparison group
selected after treatment occurred 2.one shot case study(cross-sectional
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Nonequivalent control group
Experimental and control/comparison groupdesignated before treatment occurs,not
created by random assignmentIndividual or aggregate matching used
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Mundane realism
Degree to which experiment is
superficially similar to everyday
situations
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Internal validity in experimentsfive threats
1. Selection bias-differential attrition 2. endogeneous change regression toward mean extreme scores on dep var become lessextreme on post test,testing, maturation-age,experience 3. history
effects-effect of external events-disasters 4. contamination
compensatory rivalry(John Henry effect)control group increase effortbecause denied advantage, demoralization-control group performworse because left out, Hawthorne effect-treatment group change on
dependent variable because participation make feel special
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Four types of errors in surveyresearch
1. Poor measurement-respondent satisficing whendont put forth effort 2. nonresponse-perceived benefitsof participation have declined 3. inadequate coverage
of the population-poor sampling frame 4. samplingerror-random sampling due to chance
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Field Experiment
Experimental study conducted in thefield, in real-world settings
Control over conditions is a bigproblem
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External Validation
Process of testing the validity of a measure,index,scale by examining its relation to other presumed
indicators of same variable
E.g. index of prejudice correlates with other indicatorsof prejudice
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Experimental Research
Searching for cause and effectThe classical experimental design helps usunderstand the logic of all research designs
Experiment is treated as a model againstwhich to evaluate other designs
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Experimental realism
Degree to which experiment
absorbs and involves its
participants
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Experimental group
Subjects who receive some
treatment
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Experimental design
Allows researcher to draw causalinferences and observe whether or not
the independent variable caused thedependent variable
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EPSEM-equal probability ofselection method
All members of the population have an equalchance of being selected in the sample
Is representative of the population from whichit is selected
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Elements
The individual members of the
sample
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Demonstrate Causality3 operations
1. covariation-two or more things varytogether(correlation) 2. nonspuriousness-a relation
between two variables that cannot be explained by athird variable 3. time order- demonstrate that the
assumed cause occurs first or changes prior to theassumed effect
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Demand Characteristics
Cues in an experiment that tells the participant whatbehavior is expected. In subtle ways the
experimenters words, tone of voice,gestures mayinadvertently demand desired results.To minimize
these the experimenter typically standardizesinstructions or write or tape record them.
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Criteria for CausalExplanations
1. Empirical association-variation in one variable isrelated to variation in another variable 2. appropriatetime order variation in dependent variable occurred
after the variation in the independent variable3.nonspuriousness when a relation between two
variables is not due to variation in a third variable
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Convenience sample
Researchers select a sample for studyon the basis of what is handy-e.g.
teachers using their classes
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Control group
Subjects who do not receive thetreatment
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Confidence level
The estimated probability that apopulation parameter lies within a
given confidence interval. 95 percentconfident or 99 percent conficent
C fid i l (3)
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Confidence interval (3)
Between 1Z and +1Z expect to find 68 percent of allsample means,between -1.96Z and +1.96Z find 95 % of all
sample means between -2.58Z and +2.58Z expect to find 99percent of all sample means
Confidence interval of -1.96to +1.96 about samplemean(.05),+2.58 and -2.58 is 99 out of 100,or 99 per cent
confidence interval (.01)
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Confidence interval (2)
If one knew the mean of all sample means(populationmean) and the standard deviation of these sample
means 9standard error of the mean) one couldcompute Z scores and determine the range within
which any percentage of the sample means can befound
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Confidence Interval
The range of values within whicha population parameter is
estimated to lie +-1.96 or +- 2.58
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Confidence Interval
If the distribution of sample means is normalor approximate normality, we can use the
properties of the normal curve to estimate thelocation of the population mean.
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Confederate
Person posing as a fellow participant in
an experiment who is an accomplice of
the experimenter
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Comparison group
group of subjects that is exposedto a different treatment from the
experimental group
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Weighting
Assigning different weights to cases that wereselected into a sample with different
probabilities of selection.,each case givenweight equal to the inverse of its probability of
selection