Validity generalization and hypothetical reliability distributions: A test of the Schmidt-Hunter procedure.

A Monte Carlo study was conducted to determine how variations in true reliability distributions affect validity generalization estimates that are based on hypothetical reliability distributions proposed by Schmidt and Hunter. Both interactive and noninteractive validity generalization equations were examined. True reliability distributions and sample sizes were systematically varied. Depending on the sample size and nature of the true distributions, artifactual variance was either overestimated or underestimated by both equations. In some cases, extremely large errors were observed. Even when the data were generated with true reliability distributions identical to the hypothetical distributions, both equations systematically overestimated artifactual variance. The severity of estimation errors increased proportionally as sample size per validity coefficient increased. Implications of using assumed distributions and recommendations for validity generalization researchers are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)