John C. Callender

A note on the sampling variance of the mean uncorrected correlation in meta-analysis and validity generalization.

This article compares the accuracy of several formulas for the standard error of the mean uncorrected correlation in meta-analytic and validity generalization studies. The effect of computing the mean correlation by weighting the correlation in each study by its sample size is also studied. On the basis of formal analysis and simulation studies, it is concluded that the common formula for the sampling variance of the mean correlation, V r =V/ r /K where K is the number of studies in the meta-analysis, gives reasonably accurate results. This formula gives accurate results even when sample sizes and ps are unequal and regardless of whether or not the statistical artifacts vary from study to study. It is also shown that using sample-size weighting may result in underestimation of the standard error of the mean uncorrected correlation when there are outlier sample sizes

Bias in validity generalization variance estimates: a reply to Hoben Thomas

In a recent article Thomas (1988) derived the expected value of the true validity variance estimate used in validity generalization studies. Based on computations of the expected values for certain scenarios, Thomas made a number of critical assertions regarding the variance estimate. This article shows that Thomass arguments regarding deficiencies in the variance estimate used in validity generalization studies are misleading