Literature DB >> 34672651

Meta-analysis of biodata in employment settings: Providing clarity to criterion and construct-related validity estimates.

Andrew B Speer1, Andrew P Tenbrink1, Lauren J Wegmeyer1, Caitlynn C Sendra1, Mike Shihadeh1, Sugandhjot Kaur1.   

Abstract

Although biodata inventories have long been used to hire job applicants, there are limitations to current biodata knowledge and little in the way of contemporary biodata meta-analytic reviews. This study establishes a precise understanding of biodata validity by conducting an updated meta-analysis that differentiates biodata validity in terms of two important defining features: construct domain and scoring method (rational, hybrid, empirical). Evidence was established in terms of criterion-related validity with job performance and additional work outcomes, as well as convergent validity with common external hiring measures. In total, 180 independent samples of criterion correlations were examined, and 63 samples were analyzed containing correlations with convergent measures. Findings across the meta-analyses revealed that biodata inventories are one of the most predictive assessment methods available, but that the relationship with work outcomes differs by construct domain and scoring method. Empirically scored overall composite scales had superior criterion-related validity (ρ = .44) to rationally scored composite scales (ρ = .24). Scales developed to measure conscientiousness and leadership were generally the most predictive of the job performance of the narrow construct domains, and particularly when empirically keyed. However, when biodata scores were correlated with theoretically aligned performance ratings, rational scoring resulted in similar validity coefficients as empirical scoring. Finally, biodata scales exhibited expected patterns of correlations with external measures and were only modestly correlated with cognitive ability and five-factor model personality scores. Taken together, biodata inventories are highly predictive assessment methods and are likely to provide unique variance over other common predictors. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Entities:  

Mesh:

Year:  2021        PMID: 34672651     DOI: 10.1037/apl0000964

Source DB:  PubMed          Journal:  J Appl Psychol        ISSN: 0021-9010


  1 in total

1.  Analysis of a brief biodata scale as a predictor of job performance and its incremental validity over the Big Five and Dark Tetrad personality traits.

Authors:  Pedro J Ramos-Villagrasa; Elena Fernández-Del-Río; Ángel Castro
Journal:  PLoS One       Date:  2022-09-30       Impact factor: 3.752

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.