Implications of empirical Bayes meta-analysis for test validation

Empirical Bayes meta-analysis provides a useful framework for examining tes t validation. The fixed-effects case in which rho has a single value corres ponds to the inference that the situational specificity hypothesis, can be rejected in a validity generalization study. A Bayesian analysis of such a case provides a simple and powerful test of rho = 0; such a test has practi cal implications for significance testing in test validation. The random-ef fects case in which sigma (2)(rho) > 0 provides an explicit method with whi ch to assess the relative importance of local validity studies and previous meta-analyses. Simulated data are used to illustrate both cases. Results o f published meta-analyses are used to show that local validation becomes in creasingly important a sigma (2)(rho) increases. The meaning of the term va lidity generalization is explored, and the problem of what can be inferred about test transportability in the random-effects case is described.