Patterns and Levels: Revealing Psychological Blueprints through Meta-Analytic Criterion Profile Analysis

Abstract: 

Intraindividual patterns, or configurations, serve as intuitive explanations for various phenomena and are widely recognized in both popular and scholarly discussions. Criterion Profile Analysis (CPA), as introduced by Davison & Davenport (2002), is a well-established, regression-based pattern matching procedure that identifies a pattern of predictors that optimally relate to a criterion of interest and quantifies the strength of that association. Building upon this foundation, we have advanced the methodology to use meta-analytic data, a technique we refer to as meta-analytic criterion profile analysis (MACPA), including new methods for estimating cross-validity and fungibility of criterion patterns. This presentation will outline the MACPA approach, highlighting essential methodological aspects such as homogeneity of studies in meta-analyses, corrections for statistical artifacts, and second-order sampling error. Then, I will offer examples of MACPA using organizational, educational, and personality research meta-analyses. Finally, I will present novel research that explores the influence of personality on life success criteria using MACPA. Leveraging data from 110 meta-analyses, which encompass relationships with 206 distinct variables and represent over 2.2 million participants from more than 3,200 studies, our research identified distinct personality trait profiles associated with various life success outcomes. We uncovered clusters of life success criteria and their corresponding Big Five personality profiles, offering an empirical synthesis and theoretical framework for understanding personality's impact on life success.