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Validity and Reliability Slide 2 Validity Is the translation from concept to operationalization accurately representing the underlying concept. Does your variables measure what you think in abstract concepts. This is more familiarly called Construct Validity. empirical study with high construct validity would ensure the studied parameters are relevant to the research questions. Without a valid design, valid scientific conclusions cannot be drawn Slide 3 Types of construct validity Translation validity (Trochims term) Face validity Content validity Criterion-related validity Predictive validity Concurrent validity Convergent validity Discriminant validity Slide 4 Translation validity Is the operationalization a good reflection of the construct? This approach is definitional in nature assumes you have a good detailed definition of the construct and you can check the operationalization against it. Example software success. Does your definition representative of SW success construct? E.g. Application software is a software used to assist end users. Slide 5 Discriminate where r xy is correlation between x and y, r xx is the reliability of x, and r yy is the reliability of y: a result less than.85 tells us existence of discriminant validity >.85, the two constructs overlap greatly and they are likely measuring the same thing. Slide 13 Discriminate Measuring the concept of Narcissism and Self-esteem Narcissism is a term with a wide range of meanings, usually is used to describe some kind of problem in a person or group's relationships with self and others. Self-esteem is a term in psychology to reflect a person's overall evaluation or appraisal of her or his own worth. Self-esteem encompasses beliefs (for example, "I am competent", "I am worthy") and emotions such as triumph, despair, pride and shame The Researchers show that their new scale measures Narcissism and not simply Self-esteem. Slide 14 Discriminate First, we can calculate the Average Inter-Item Correlations within and between the two scales: Narcissism Narcissism: 0.47 Narcissism Self-esteem: 0.30 Self-esteem Self-esteem: 0.52 We then use the correction for attenuation formula: Slide 15 Discriminate Since 0.607 is less than 0.85, we can conclude that discriminant validity exists between the scale measuring narcissism and the scale measuring self-esteem. e.g., a new measure of depression should have negative correlations with measures of happiness have minimal correlations with tests of physical health, Slide 16 Internal and External Validity Slide 17 Internal Validity Inferences are said to possess internal validity if a causal relation between two variables is properly demonstrated. A causal inference may be based on a relation when three criteria are satisfied: 1. the "cause" precedes the "effect" in time (temporal precedence), 2. the "cause" and the "effect" are related (covariation), and 3. there are no plausible alternative explanations for the observed covariation Slide 18 Example - Internal The researcher hypothesized that computer training will increase software usability Training (IV) and usability (DV) Positive correlation between the two indicates high internal validity. This can be done with Spearman Rank Correlation or Pearson Correlation Can be easily done with SPSS software Slide 19 Internal In many cases, however, the magnitude of effects found in the dependent variable may not just depend on variations in the independent variable, the power of the instruments and statistical procedures used to measure and detect the effects, and the choice of statistical methods Other variables or circumstances uncontrolled for (or uncontrollable) may lead to additional or alternative explanations (a) for the effects found and/or (b) for the magnitude of the effects found. Slide 20 Internal highly controlled true experimental designs, i.e random selection, random assignment to either the control or experimental groups, reliable instruments, reliable manipulation processes, and safeguards against confounding factors may be the "gold standard" of scientific research. the very strategies employed to control these factors may also limit the generalizability or External Validity of the findings. Slide 21 External validity external validity refers to the applicability of study or experimental results to realms beyond those under immediate observation. Refers to generalizability of the research finding to other similar cases Does the software solution for one case is also applicable to other similar cases in other organization or country. Does the solution has wider application and audience or acceptance. We need that solution! Researchers prize studies with external validity, since the results can be widely applied to other scenarios. Slide 22 External External validity for a given study has several aspects: 1. whether the study generalizes to other subjects in the domain 2. whether there exist enough evidence and arguments to support the claimed generalizability 3. whether the study outcomes validate predicted theories Slide 23 Reliability Means "repeatability" or "consistency". A measure is considered reliable if it would give us the same result over and over again (assuming that what we are measuring isn't changing!). Measuring the same distance at different times should give the same result if the instrument (e.g. meter) is reliable. There are four general classes of reliability estimates, each of which estimates reliability in a different way. Slide 24 Types of Reliability Estimation 24 Inter-rater or inter-observer reliability Is used to assess consistency of different raters Test-retest reliability Is used to assess the consistency of a measure from one time to another Parallel-forms reliability Is used to assess the consistency of the results of two tests constructed in the same way from the same content domain Internal consistency reliability Is used to assess the consistency of results across items within a test Slide 25 Inter-Rater or Inter-Observer Reliability Used to assess the degree to which different raters/observers give consistent estimates of the same phenomenon. Establish reliability on pilot data or a subsample of data and retest often throughout. For categorical data a X 2 (Chai sqaure) can be used and for continuous data an R (regression) can be calculated. Slide 26 Test-Retest Reliability Used to assess the consistency of a measure from one time to another. This approach assumes that there is no substantial change in the construct being measured between the two occasions. The amount of time allowed between measures is critical. The shorter the time gap, the higher the correlation; the longer the time gap, the lower the correlation Slide 27 Parallel-Forms Reliability Used to assess the consistency of the results of two tests constructed in the same way from the same content domain. Create a large set of questions that address the same construct and then randomly divide the questions into two sets and administer both instruments to the same sample of people. The correlation between the two parallel forms is the estimate of reliability. One major problem with this approach is that you have to be able to generate lots of items that reflect the same construct. Slide 28 Split Half Reliability Collect your data with the instrument to measure your construct. Split the data into halve and do correlation between the two data sets Positive correlation indicates high reliability Slide 29 Reliability and Validity 29 Slide 30 Research Ethics Slide 31 Ethics a definition 31 Research should avoid causing harm, distress, anxiety, pain or any other negative feeling to participants. Participants should be fully informed about all relevant aspects of the research, before they agree to take part [1] Slide 32 ARE YOU HOMOSEXUAL? 24 Nov 2008 Research Methodology 32 THIS IS A HYPOTHETICAL QUESTION - DO NOT ANSWER THIS Slide 33 Research questions ethical or not? 33 Research may ask a taboo or personal question What if you were asked if you are homosexual How would you feel if you were asked this? Would you feel awkward? Would you lie? Would you answer truthfully? Why are we asking this question anyway? Could we phrase the question better? Slide 34 Pause for thought 34 Is it morally correct to carry out research by any means whatsoever providing that the end result increases the sum of human knowledge or provides some tangible benefit to mankind? Does the end justify the means? DISCUSS Slide 35 Ethics before Research begins 35 Inform all participants fully What about children Mentally deficient people Those with poor language skills Obtain consent Define the gatekeeper Craft your research methods carefully No distortion of the data Slide 36 Ethics during Research Research Methodoogy 36 Field notes what are they? Do we need these? Can we use these in our research? Consent issues Content issues Moral issues You have heard about a crime do you report it? DISCUSS Slide 37 Confidentiality of respondent data 37 How do we keep track of respondents? Should we keep track of respondents? How do we de-personalise gathered data? If data are depersonalised, is it morally correct to reuse this data for a new research project? DISCUSS Slide 38 Ethics after Research 38 Disposal of data paper or digital? Freedom of Information Act Reuse of data is this ethical? Are there occasions where reuse of gathered data for another purpose is ok? Requesting permission from respondents Difficulties of contacting original respondents Slide 39 Engineering and Ethics 39 Confidentiality of data Ownership of research results Consider research results Is a cure for a disease as the direct result of research good? Is the creation of a powerful bomb as the direct result of research good? e.g. the atom bomb DISCUSS Slide 40 Research Ethics Committees 40 Monitor ethical issues in research programmes Before during and after research Makes decisions and enforces these Gives researchers organisational support Reassurance to researchers about moral issues related to a particular research project Slide 41 Plagiarism 41 What is plagiarism? How do we avoid plagiarism? What are the dangers that plagiarism causes? State some examples of plagiarism. DISCUSS Slide 42 Summary - Ethics Ethics are moral issues relating to the prior design, gathering and usage of data for research purposes Think before, during and after Consult gatekeepers and respondents Never act alone consult your supervisor if in doubt