TY - JOUR
T1 - Meta-analytic five-factor model personality intercorrelations
T2 - Eeny, meeny, miney, moe, how, which, why, and where to go.
AU - Park, Hye Soo (Hailey)
AU - Wiernik, Brenton M.
AU - Oh, In Sue
AU - Gonzalez-Mulé, Erik
AU - Ones, Deniz S.
AU - Lee, Youngduk
N1 - Publisher Copyright:
© 2020 American Psychological Association
PY - 2020
Y1 - 2020
N2 - Meta-analysis is frequently combined with multiple regression or path analysis to examine how the Big Five/Five-Factor Model (FFM) personality traits relate to work outcomes. A common approach in such studies is to construct a synthetic correlation matrix by combining new meta-analyses of FFM–criterion correlations with previously published meta-analytic FFM intercorrelations. Many meta-analytic FFM intercorrelation matrices exist in the literature, with 3 matrices being frequently used in industrial-organizational (I-O) psychology and related fields (i.e., Mount, Barrick, Scullen, & Rounds, 2005; Ones, 1993; van der Linden, te Nijenhuis, & Bakker, 2010). However, it is unknown how the choice of FFM matrix influences study conclusions, why we observe such differences in the matrices, and which matrix researchers and practitioners should use for their specific studies. We conducted 3 studies to answer these questions. In Study 1, we demonstrate that researchers’ choice of FFM matrix can substantively alter conclusions from meta-analytic regressions or path analyses. In Study 2, we present a new meta-analysis of FFM intercorrelations using measures explicitly constructed around the FFM and based on employee samples. In Study 3, we systematically explore the sources of differences in FFM intercorrelations using second-order meta-analyses of 44 meta-analytic FFM matrices. We find that personality rating source (self vs. other) and inventory-specific substantive and methodological features are the primary moderators of meta-analytic FFM intercorrelations. Based on the findings from these studies, we provide a framework to guide future researchers in choosing a meta-analytic FFM matrix that is most appropriate for their specific studies, research questions, and contexts.
AB - Meta-analysis is frequently combined with multiple regression or path analysis to examine how the Big Five/Five-Factor Model (FFM) personality traits relate to work outcomes. A common approach in such studies is to construct a synthetic correlation matrix by combining new meta-analyses of FFM–criterion correlations with previously published meta-analytic FFM intercorrelations. Many meta-analytic FFM intercorrelation matrices exist in the literature, with 3 matrices being frequently used in industrial-organizational (I-O) psychology and related fields (i.e., Mount, Barrick, Scullen, & Rounds, 2005; Ones, 1993; van der Linden, te Nijenhuis, & Bakker, 2010). However, it is unknown how the choice of FFM matrix influences study conclusions, why we observe such differences in the matrices, and which matrix researchers and practitioners should use for their specific studies. We conducted 3 studies to answer these questions. In Study 1, we demonstrate that researchers’ choice of FFM matrix can substantively alter conclusions from meta-analytic regressions or path analyses. In Study 2, we present a new meta-analysis of FFM intercorrelations using measures explicitly constructed around the FFM and based on employee samples. In Study 3, we systematically explore the sources of differences in FFM intercorrelations using second-order meta-analyses of 44 meta-analytic FFM matrices. We find that personality rating source (self vs. other) and inventory-specific substantive and methodological features are the primary moderators of meta-analytic FFM intercorrelations. Based on the findings from these studies, we provide a framework to guide future researchers in choosing a meta-analytic FFM matrix that is most appropriate for their specific studies, research questions, and contexts.
KW - Big Five
KW - Five-Factor Model of personality
KW - meta-analysis
KW - meta-regression
KW - second-order meta-analysis
UR - http://www.scopus.com/inward/record.url?scp=85082761338&partnerID=8YFLogxK
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U2 - 10.1037/apl0000476
DO - 10.1037/apl0000476
M3 - Article
C2 - 32150423
AN - SCOPUS:85082761338
SN - 0021-9010
VL - 105
SP - 1490
EP - 1529
JO - Journal of Applied Psychology
JF - Journal of Applied Psychology
IS - 12
ER -