Validity generalization and situational specificity: A second look at the 75% rule and Fisher's z transformation.

In this article we analyzed the James, Demaree, and Mulaik (1986) critique of validity generalization. We demonstrated that the James et al. article (a) is not relevant to the real-world use of validity generalization in organizations, (b) has overlooked the bulk of the evidence against the situational specificity hypothesis and, therefore, the substantive conclusion that the situational specificity hypothesis is alive and well cannot be supported, and (c) has confused the processes of hypothesis testing and parameter estimation in validity generalization and has made incorrect statements about the assumptions underlying both. In addition, (d) James et al.'s critique of the 75% rule is a statistical power argument and, as such, does not add to earlier statistical power studies; (e) the procedures for use of confidence intervals that they advocate are erroneous; (f) there is no double correction of artifacts in validity generalization, as they contend; (g) the bias in the correlation (r) and the sampling error formula for r that they discuss is well-known, trivial in magnitude, and has no empirical significance; and (h) the use of the Fisher's z transformation of r in validity generalization studies and other meta-analyses (which they advocate) creates an unnecessary inflationary bias in estimates of true validities and provides no benefits. In light of these facts, we conclude that the James et al. substantive conclusions and methodological recommendations are seriously flawed. This article is an analysis of the James, Demaree, and Muliak (1986) critique of validity generalization methods and conclusions, a long and detailed article. In the interests of brevity, we will focus only on those portions of James et al. that we judge to be most in need of critical evaluation. Their remaining arguments are left to the reader to evaluate in light of the analysis presented here.