Revisiting predictor–criterion construct congruence: Implications for designing personnel selection systems

By contrast, construct-based congruence aligns employment tests of job-relevant KSAOs (e.g., verbal and math skills, conscientiousness) with relevant work criteria, such as technical performance or counterproductive work behavior (e.g., Campbell & Wiernik, 2015). A lack of predictor–criterion co...

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Published inIndustrial and organizational psychology Vol. 16; no. 3; pp. 307 - 312
Main Authors Hough, Leaetta M., Oswald, Frederick L.
Format Journal Article
LanguageEnglish
Published New York, USA Cambridge University Press 01.09.2023
Subjects
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ISSN1754-9426
1754-9434
DOI10.1017/iop.2023.35

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Abstract By contrast, construct-based congruence aligns employment tests of job-relevant KSAOs (e.g., verbal and math skills, conscientiousness) with relevant work criteria, such as technical performance or counterproductive work behavior (e.g., Campbell & Wiernik, 2015). A lack of predictor–criterion congruence is an important source of error contributing to meta-analytic correlations, where correlations could increase (due to method variance such as likability in both the interview and in performance ratings; Schmitt et al., 1996) or correlations could decrease (due to KSAO incongruence). In a world where selection systems are subject to government regulations, and social justice requires that those systems be fair to all, strategies that rely on known inputs and produce known outcomes such as through predictor–criterion construct congruence as enabled through synthetic validity strategies are key to successful design of selection systems. [...]when predictor–criterion construct congruence is high, validity coefficients are not only higher, they stand to be more consistent across samples (validity coefficients that are less likely to capitalize on chance).
AbstractList By contrast, construct-based congruence aligns employment tests of job-relevant KSAOs (e.g., verbal and math skills, conscientiousness) with relevant work criteria, such as technical performance or counterproductive work behavior (e.g., Campbell & Wiernik, 2015). A lack of predictor–criterion congruence is an important source of error contributing to meta-analytic correlations, where correlations could increase (due to method variance such as likability in both the interview and in performance ratings; Schmitt et al., 1996) or correlations could decrease (due to KSAO incongruence). In a world where selection systems are subject to government regulations, and social justice requires that those systems be fair to all, strategies that rely on known inputs and produce known outcomes such as through predictor–criterion construct congruence as enabled through synthetic validity strategies are key to successful design of selection systems. [...]when predictor–criterion construct congruence is high, validity coefficients are not only higher, they stand to be more consistent across samples (validity coefficients that are less likely to capitalize on chance).
Author Hough, Leaetta M.
Oswald, Frederick L.
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SubjectTerms Assessment centers
Behavior
Cognitive ability
Commentaries
Employment
Employment interviews
Job performance
Meta-analysis
Personnel selection
Validity
Title Revisiting predictor–criterion construct congruence: Implications for designing personnel selection systems
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