Publication Type
Journal Article
Version
submittedVersion
Publication Date
9-2008
Abstract
Previous research on the validity and adverse impact (AI) of predictor composite formation focused on the merits of regression-based or ad hoc composites. We argue for a broader focus. Ad hoc chosen composites are usually not Pareto-optimal, whereas the regression-based composite represents only one element from the total set of Pareto-optimal composites and can, therefore, provide only limited information on the potential for validity and AI reduction of forming predictor composites when both validity and AI are of concern. In that case, other Pareto-optimal composites may provide a better benchmark to decide on the merits of the predictor composite formation. We summarize a method to determine the set of Pareto-optimal composites and apply the method to a representative collection of selection predictors. The application shows that the assessment of the AI and validity of predictor composite formation can differ substantially from the one arrived at when considering only regression-based composites.
Discipline
Human Resources Management | Industrial and Organizational Psychology
Research Areas
Organisational Behaviour and Human Resources
Publication
International Journal of Selection and Assessment
Volume
16
Issue
3
First Page
183
Last Page
194
ISSN
0965-075X
Identifier
10.1111/j.1468-2389.2008.00423.x
Publisher
Wiley: 24 months
Citation
DE CORTE, Wilfried; LIEVENS, Filip; and SACKETT, Paul R..
Validity and adverse impact potential of predictor composite formation. (2008). International Journal of Selection and Assessment. 16, (3), 183-194.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/5630
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1111/j.1468-2389.2008.00423.x