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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) …
Robustness, Sensitivity And Sampling Variability Of Pareto-Optimal Selection System Solutions To Address The Quality-Diversity Trade-Off, Wilfried De Corte, Paul Sackett, Filip Lievens
Robustness, Sensitivity And Sampling Variability Of Pareto-Optimal Selection System Solutions To Address The Quality-Diversity Trade-Off, Wilfried De Corte, Paul Sackett, Filip Lievens
Research Collection Lee Kong Chian School Of Business
In case that both the goals of selection quality and diversity are important, a selection system is Pareto-optimal (PO) when its implementation is expected to result in an optimal balance between the levels achieved with respect to both these goals. The study addresses the critical issue whether PO systems, as computed from calibration conditions, continue to perform well when applied to a large variety of different validation selection situations. To address the key issue, we introduce two new measures for gauging the achievement of these designs and conduct a large simulation study in which we manipulate 10 factors (related to …
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 …
Personnel Selection, Paul R. Sackett, Filip Lievens
Personnel Selection, Paul R. Sackett, Filip Lievens
Research Collection Lee Kong Chian School Of Business
We review developments in personnel selection since the previous review by Hough & Oswald (2000) in the Annual Review of Psycholog. We organize the review around a taxonomic structure of possible bases for improved selection, which includes (a) better understanding of the criterion domain and criterion measurement, (b) improved measurement of existing predictor methods or constructs, (c) identification and measurement of new predictor methods or constructs, (d) improved identification of features that moderate or mediate predictor-criterion relationships, (e) clearer understanding of the relationship between predictors or between predictors and criteria (e.g., via meta-analytic synthesis), (f) identification and prediction of new …
Combining Predictors To Achieve Optimal Trade-Offs Between Selection Quality And Adverse Impact, Wilfried De Corte, Filip Lievens, Paul R. Sackett
Combining Predictors To Achieve Optimal Trade-Offs Between Selection Quality And Adverse Impact, Wilfried De Corte, Filip Lievens, Paul R. Sackett
Research Collection Lee Kong Chian School Of Business
The authors propose a procedure to determine (a) predictor composites that result in a Pareto-optimal trade-off between the often competing goals in personnel selection of quality and adverse impact and (b) the relative importance of the quality and impact objectives that correspond to each of these trade-offs. They also investigated whether the obtained Pareto-optimal composites continue to perform well under variability of the selection parameters that characterize the intended selection decision. The results of this investigation indicate that this is indeed the case. The authors suggest that the procedure be used as one of a number of potential strategies for …
Predicting Adverse Impact And Mean Criterion Performance In Multistage Selection, Wifried De Corte, Filip Lievens, Paul R. Sackett
Predicting Adverse Impact And Mean Criterion Performance In Multistage Selection, Wifried De Corte, Filip Lievens, Paul R. Sackett
Research Collection Lee Kong Chian School Of Business
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 …
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.