Understanding Individual Personality Structures Through Idiographic Factor Analysis and Network Models

要旨

Abstract Understanding individual personality requires methods that capture within‐person variability rather than relying solely on between‐person models, such as the Big Five. This study aimed to elucidate individual personality structures by conducting factor analyses on longitudinal Big Five indicators and applying graphical vector autoregression (GVAR) models to reveal the dynamic interactions among factors. Five female undergraduates completed a 30‐item questionnaire daily for approximately 90 days, allowing us to identify idiographic factors specific to each participant. Results revealed significant heterogeneity in factor structures and network dynamics, challenging the assumption of ergodicity in Big Five indicators. Moreover, while similar factors emerged across participants, their network relationships varied considerably, highlighting the need for individualized approaches to personality research. This study highlights the importance of integrating idiographic methods to achieve a nuanced understanding of individual personalities and encourages future research to further develop methodologies that better capture individuality.

主題