How to conduct reliability and validity tests for self-reported surveys?

Reliability and validity testing is essential for establishing the psychometric quality of self-reported survey instruments, confirming measurement consistency (reliability) and accuracy in measuring the intended constructs (validity). These psychometric evaluations are fundamental for ensuring data integrity and the credibility of subsequent analyses. Key principles involve assessing multiple reliability facets (internal consistency, test-retest, inter-rater) and gathering different forms of validity evidence (content, criterion-related, construct). Necessary conditions include a clear theoretical definition of constructs, appropriate sample size and representativeness, and well-designed survey items. Core considerations are using established statistical thresholds (e.g., Cronbach's alpha ≥ 0.7 for internal consistency reliability), employing multiple methods for triangulating validity evidence, and ensuring the scale functions consistently across different groups when applicable. Implementation involves developing the instrument based on construct definitions and expert review (content validity). After pilot testing, administer the survey to the target sample. Calculate reliability coefficients (e.g., Cronbach's alpha, ICCs). For validity, correlate scores with relevant external criteria (criterion validity), perform exploratory and confirmatory factor analysis (construct validity), and test for measurement invariance if comparing groups. Results must be interpreted against benchmarks to confirm instrument adequacy before substantive data analysis.