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DERIVATION AND IMPLICATIONS OF A META‐ANALYTIC MATRIX INCORPORATING COGNITIVE ABILITY, ALTERNATIVE PREDICTORS, AND JOB PERFORMANCE
Author(s) -
BOBKO PHILIP,
ROTH PHILIP L.,
POTOSKY DENISE
Publication year - 1999
Publication title -
personnel psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.076
H-Index - 142
eISSN - 1744-6570
pISSN - 0031-5826
DOI - 10.1111/j.1744-6570.1999.tb00172.x
Subject(s) - psychology , construct (python library) , cognition , meta analysis , personnel selection , selection (genetic algorithm) , field (mathematics) , cognitive psychology , job performance , applied psychology , variety (cybernetics) , social psychology , matrix (chemical analysis) , management science , job satisfaction , computer science , statistics , artificial intelligence , economics , mathematics , medicine , materials science , neuroscience , pure mathematics , composite material , programming language
A variety of recent articles in the personnel selection literature have used analyses of meta‐analytically derived matrices to draw general conclusions for the field. The purpose of this article is to construct a matrix that incorporates as complete information as possible on the relationships among cognitive ability measures, three sets of alternative predictors, and job performance, We build upon a starting matrix used by Schmitt, Rodgers, Chan, Sheppard, and Jennings (1997). Mean differences, by race, for each of the measures and the potential for adverse impact of predictor composites are also considered. We demonstrate that the use of alternative predictors alone to predict job performance (in the absence of cognitive ability) lowers the potential for adverse impact. However, in contrast to recent claims, adverse impact continues to occur at many commonly used selection ratios. Future researchers are encouraged to use our matrix and to expand upon it as new primary research becomes available. We also report and reaffirm many methodological lessons along the way, including the many judgment calls that appear in an effort of this magnitude and a reminder that the field could benefit from even greater conceptual care regarding what is labeled an “alternative predictor.” Directions for future meta‐analyses and for future primary research activities are also derived.