title: Predicting adverse impact and mean criterion performance in multistage selection.
abstract: The authors present an analytical method to assess the average criterion performance of the selected candidates as well as the adverse impact and the cost of general multistage selection decisions. The method extends previous work on the analytical estimation of multistage selection outcomes to the case in which the applicant pool is a mixture of applicant populations that differ in their average performance on the selection predictors. Next, the method was used to conduct 3 studies of important issues practitioners and researchers have with multistage selection processes. Finally, the authors indicate how the method can be integrated into a broader analytical framework to design multistage selection decisions that achieve intended levels of selection cost, workforce quality, and workforce diversity.
authors.affiliation: Ghent University, Department of Data Analysis, Ghent, Belgium. wilfried.decorte@rug.ac.be
authors.forename: Wilfried
authors.initials: W
authors.lastname: De Corte
authors.forename: Filip
authors.initials: F
authors.lastname: Lievens
authors.forename: Paul R
authors.initials: PR
authors.lastname: Sackett
mesh_terms: D004650:Employee Performance Appraisal / Q000706:statistics & numerical data*; D004651:Employment / Q000706:statistics & numerical data*; D006801:Humans; D009010:Monte Carlo Method; D010560:Personnel Selection; D000078329:Workforce