Longitudinal within-person variability around personality trajectories

Decades of research has identified average patterns of normative personality development across the lifespan. However, it is unclear how well these correspond to trajectories of individual development. Past work beyond general personality development might suggest these average patterns are oversimplifications, necessitating novel examinations of how personality develops and consideration of new individual difference metrics. This study uses five longitudinal datasets from Germany, Australia, the Netherlands, and the United States (N = 128,345; Mage = 45.42; 53% female) to examine personality development using Mixed-Effects Location Scale Models. These models quantify individual differences in within-person residual variability, or sigma, around trajectories – thereby testing if models that assume sigma is homogeneous, unsystematic noise are appropriate. We investigate if there are individual differences in longitudinal within-person variability for Big Five trajectories; if there are variables associated with this heterogeneity; and if person-level sigma values can uniquely predict an outcome. Results indicated that, across all models, there was meaningful heterogeneity in sigma – the magnitude of which was comparable to and often even greater than that of intercepts and slopes. Individual differences in sigma were further associated with covariates central to personality development and had robust predictive utility for health status, an outcome with long-established personality associations. Collectively, these findings underscore the presence, degree, validity, and potential utility of heterogeneity in longitudinal within-person variability and indicate the typical linear model does not adequately depict individual development. We suggest it should become the default to consider this individual difference metric in personality development research.