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Changes in personality are often modeled linearly or curvilinearly. It is a simplifying—yet untested—assumption that the chosen sample-level model form accurately depicts all person-level trajectories within the sample. Given the complexity of personality development, it seems unlikely that imposing a single model form across all individuals is appropriate. Although typical growth models can estimate individual trajectories that deviate from the average via random effects, they do not explicitly test whether people differ in the forms of their trajectories. This heterogeneity is valuable to uncover, though, as it may imply that different processes are driving change. The present study uses data from four longitudinal data sets (N = 26,469; Mage = 47.55) to empirically test the degree that people vary in best-fitting model forms for their Big Five personality development. Across data sets, there was substantial heterogeneity in best-fitting forms. Moreover, the type of form someone had was directly associated with their net and total amount of change across time, and these changes were substantially misquantified when a worse-fitting form was used. Variables such as gender, age, trait levels, and number of waves were also associated with people’s types of forms. Lastly, comparisons of best-fitting forms from individual- and sample-level models indicated that consequential discrepancies arise from different levels of analysis (i.e., individual vs. sample) and alternative modeling choices (e.g., choice of time metric). Our findings highlight the importance of these individual differences for understanding personality change processes and suggest that a flexible, person-level approach to understanding personality development is necessary. (PsycInfo Database Record (c) 2024 APA, all rights reserved)
