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.