Individual differences in effects of life events on personality trait change

The overall aim of this dissertation is to investigate individual differences in the impact of major life events on different types of personality trait change. In the first paper, I introduce a statistical modeling approach, which builds on the revised Latent State-Trait (LST-R) Theory and Moderated Nonlinear Factor Analysis and is termed Moderated Nonlinear Latent State Trait (MNLST) modeling. The framework allows to model individual differences in mean-level changes, changes in trait variance and situational variability as represented in LST-R models by linking key parameters to various types of external covariates. The MNLST approach is illustrated with an application to real data and examined with a simulation study. In the second paper, I propose a new inventory for the assessment of life events, the Critical Life Event Categories Scale (CLECS) which captures 21 broader, but content-homogenous life event categories and also takes their individual perception in terms of valence and controllability into account. The frequency of the occurrence of life event categories is examined in time-intervals from one month to four years. I also investigate the predictive validity of the occurrence of life events and the nomological validity of life event perceptions. In the third paper, the MNLST approach and the CLECS are utilized to investigate individual differences in the effects of life events on different types of personality trait change. Age, gender, the individual perception of life events and their repeated occurrence are investigated as moderators of life event effects. I also examine the time-dependence of life event effects and compare self- and informant reports of personality in terms of trait change following life events.