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Contents
- Abstract
- Study 1: Impact of FFM Matrix Choice on Substantive Conclusions
- Study 1 Method
- Literature search
- Inclusion criteria and analyses
- Study 1 Results
- Entrepreneurship
- Leadership
- Job attitudes
- Motivation
- Job performance
- Meta-analytic path analysis—Judge et al. (2007)
- Study 1 Discussion
- Study 2: A New Meta-Analytic FFM Matrix Using Explicit FFM Scales and Employee Samples
- Study 2 Method
- Literature search
- Inclusion and exclusion criteria
- Coding procedure
- Meta-analytic procedures
- Study 2 Results and Discussion
- Study 3: Investigating Sources of Differences in FFM Intercorrelations
- Second-Order Sampling Error
- Rating Source
- Personality Inventory Characteristics
- Personality construct conceptualization
- Personality framework
- Inventory method effects
- Potential inventory characteristic moderator variables
- Sample Type and Assessment Purpose
- Publication Status
- International Samples
- Year of Data Collection
- Study 3 Method
- Meta-analytic FFM matrices
- Potential moderator variables
- Analyses
- Study 3 Results and Discussion
- Second-order meta-regression results
- Within- versus between-inventory
- Personality framework
- Specific inventory
- Sample type
- Unpublished studies
- Other potential moderators
- Assessment purpose
- United States/North America-only studies
- Multiple meta-regressions
- Overall Discussion
- How Should Meta-Analysts Choose an FFM Intercorrelation Matrix?
- What is the best approach?
- Caveat: What if studies use nonself-ratings?
- Caveat: What if studies use unusual personality measures?
- What if constructing a custom synthetic correlation matrix is infeasible?
- What if studies use only explicit FFM measures?
- What if studies use a small number of classified FFM measures or other-ratings?
- What if studies use a large number of classified FFM measures?
- Other recommendations and considerations
- Limitations and Future Research Directions
- Conclusion
Figures and Tables
Abstract
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,...