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A Comprehensive Examination Of The Cross-Validity Of Pareto-Optimal Versus Fixed-Weight Selection Systems In The Biobjective Selection Context., Wilfried De Corte, Filip Lievens, Paul R. Sackett
A Comprehensive Examination Of The Cross-Validity Of Pareto-Optimal Versus Fixed-Weight Selection Systems In The Biobjective Selection Context., Wilfried De Corte, Filip Lievens, Paul R. Sackett
Research Collection Lee Kong Chian School Of Business
The article presents evidence for the cross-validity potential of fixed-weight (FW) versus Pareto-Optimal (PO) selection systems in biobjective selection situations where both the goals of diversity and quality are valued and the importance of the goals is undecided a priori. The article extends previous research by also studying the cross-validity potential of selection systems in the practically most important sample-to-sample cross-validity scenario. We address three research questions: (a) Do different PO systems show comparable levels of relative (i.e., proportional) achievement upon cross-validation? (b) Do PO systems achieve higher levels of relative achievement upon cross-validation than FW selection systems?, and (c) …
Designing Pareto-Optimal Selection Systems: Formalizing The Decisions Required For Selection System Development, Wilfried De Corte, Paul R. Sackett, Filip Lievens
Designing Pareto-Optimal Selection Systems: Formalizing The Decisions Required For Selection System Development, Wilfried De Corte, Paul R. Sackett, Filip Lievens
Research Collection Lee Kong Chian School Of Business
The article presents an analytic method for designing Pareto-optimal selection systems where the applicants belong to a mixture of candidate populations. The method is useful in both applied and research settings. In an applied context, the present method is the first to assist the selection practitioner when deciding on 6 major selection design issues: (1) the predictor subset, (2) the selection rule, (3) the selection staging, (4) the predictor sequencing, (5) the predictor weighting, and (6) the stage retention decision issue. From a research perspective, the method offers a unique opportunity for studying the impact and relative importance of different …
The Risk Of Adverse Impact In Selections Based On A Test With Known Effect Size, Wilfried De Corte, Filip Lievens
The Risk Of Adverse Impact In Selections Based On A Test With Known Effect Size, Wilfried De Corte, Filip Lievens
Research Collection Lee Kong Chian School Of Business
The authors derive the exact sampling distribution function of the adverse impact (AI) ratio for single-stage, top-down selections using tests with known effect sizes. Subsequently, it is shown how this distribution function can be used to determine the risk that a future selection decision on the basis of such tests will result in an outcome that reflects the presence of AI. The article therefore provides test and selection practitioners with a valuable tool to decide between alternative selection predictors.