Newman Daniel A, Jacobs Rick R, Bartram Dave
Department of Psychology, Texas A&M University, College Station 77843-4235, USA.
J Appl Psychol. 2007 Sep;92(5):1394-413. doi: 10.1037/0021-9010.92.5.1394.
This study assessed the relative accuracy of 3 techniques--local validity studies, meta-analysis, and Bayesian analysis--for estimating test validity, incremental validity, and adverse impact in the local selection context. Bayes-analysis involves combining a local study with nonlocal (meta-analytic) validity data. Using tests of cognitive ability and personality (conscientiousness) as predictors, an empirically driven selection scenario illustrates conditions in which each of the 3 estimation techniques performs best. General recommendations are offered for how to estimate local parameters, based on true population variability and the number of studies in the meta-analytic prior. Benefits of empirical Bayesian analysis for personnel selection are demonstrated, and equations are derived to help guide the choice of a local validity technique (i.e., meta-analysis vs. local study vs. Bayes-analysis).
本研究评估了三种技术——局部效度研究、元分析和贝叶斯分析——在局部选拔情境中估计测验效度、增量效度和不利影响方面的相对准确性。贝叶斯分析涉及将局部研究与非局部(元分析)效度数据相结合。以认知能力测试和人格(尽责性)作为预测指标,一个基于实证的选拔情境说明了三种估计技术各自表现最佳的条件。基于总体真实变异性和元分析先验中的研究数量,针对如何估计局部参数给出了一般性建议。证明了实证贝叶斯分析在人员选拔中的益处,并推导了方程以帮助指导局部效度技术(即元分析与局部研究与贝叶斯分析)的选择。