The stability of individual differences is a fundamental issue in personality psychology. Although accumulating evidence suggests that many psychological attributes are both stable and change over time, existing research rarely takes advantage of theoretical models that capture both stability and change. In this article, we present the Meta-Analytic Stability and Change model (MASC), a novel meta-analytic model for synthesizing data from longitudinal studies. MASC is based on trait-state models that can separate influences of stable and changing factors from unreliable variance (Kenny & Zautra, 1995). We used MASC to evaluate the extent to which personality traits, life satisfaction, affect, and self-esteem are influenced by these different factors. The results showed that the majority of reliable variance in personality traits is attributable to stable influences (83%). Changing factors had a greater influence on reliable variance in life satisfaction, self-esteem, and affect than in personality (42%-56% vs. 17%). In addition, changing influences on well-being were more stable than changing influences on personality traits, suggesting that different changing factors contribute to personality and well-being. Measures of affect were less reliable than measures of the other 3 constructs, reflecting influences of transient factors, such as mood on affective judgments. After accounting for differences in reliability, stability of affect did not differ from other well-being variables. Consistent with previous research, we found that stability of individual differences increases with age. (PsycINFO Database Record

In light of consistently observed correlations among Big Five ratings, the authors developed and tested a model that combined E. L. Thorndike's (1920) general evaluative bias (halo) model and J. M. Digman's (1997) higher order personality factors (alpha and beta) model. With 4 multitrait-multimethod analyses, Study 1 revealed moderate convergent validity for alpha and beta across raters, whereas halo was mainly a unique factor for each rater. In Study 2, the authors showed that the halo factor was highly correlated with a validated measure of evaluative biases in self-ratings. Study 3 showed that halo is more strongly correlated with self-ratings of self-esteem than self-ratings of the Big Five, which suggests that halo is not a mere rating bias but actually reflects overly positive self-evaluations. Finally, Study 4 demonstrated that the halo bias in Big Five ratings is stable over short retest intervals. Taken together, the results suggest that the halo-alpha-beta model integrates the main findings in structural analyses of Big Five correlations. Accordingly, halo bias in self-ratings is a reliable and stable bias in individuals' perceptions of their own attributes. Implications of the present findings for the assessment of Big Five personality traits in monomethod studies are discussed.

A nationally representative panel study of British households was used to examine the extent to which Big Five personality traits interact with the experience of major life events (marriage, childbirth, unemployment, and widowhood) to predict increases and decreases in life satisfaction following the event. Results show that major life events are associated with changes in life satisfaction, and some of these changes are very long lasting. Personality traits did not have consistent moderating effects on the association between stressful life events and life satisfaction over time.

Set-point theory posits that individuals react to the experience of major life events, but quickly adapt back to pre-event baseline levels of subjective well-being in the years following the event. A large, nationally representative panel study of Swiss households was used to examine set-point theory by investigating the extent of adaptation following the experience of marriage, childbirth, widowhood, unemployment, and disability. Our results demonstrate that major life events are associated with marked change in life satisfaction and, for some events (e.g., marriage, disability), these changes are relatively long lasting even when accounting for normative, age related change.

The Day Reconstruction Method is a useful tool for evaluating short-term changes in emotional experiences over a variety of daily situations. However, traditional method of collecting DRM data can be time-intensive for both researchers and participants. In this paper we provide evidence that a random-sampling approach to DRM assessment can provide useful data that are largely consistent with previous research that used the full version of the DRM. In a nationally representative sample of 2,303 people, we demonstrate that (1) there is variability in emotional ratings of episodes that replicates what has been found in prior studies, (2) correlations with global measures are typically small in magnitude (< .30), (3) correlations with personality are for the most part negligible, (4) correlations with global ratings of domain satisfaction are higher for domain-relevant situations, and (5) parents report more positive affect while providing care for their children when compared to other activities, and this effect can account for the observed differences in emotional experiences of parents and non-parents.