Theses and Dissertations Collection

Although a variety of statistical methods are available for analyzing longitudinal data, modeling the dynamics of a complex structural model remains a difficult methodological challenge. In this thesis, an Autoregressive Structural Model (ASM) was developed to exam- ine the relationships between social activity, physical activity, and functional health status (‘factors’) on depressive symptoms while accounting for temporal dependence. The ASM builds on an autoregressive model for repeated measurements and incorporates a structural equation model that delineates the mechanism among the factors. We applied the ASM to elucidate the impact of these factors on depressive symptoms in the China Health and Retirement Longitudinal Study (CHARLS), a multi-year study of aging involving 20,000 participants 45 years of age and older. The results indicate that social and physical activity independently and consistently mitigated depressive symptoms over the course of five years, by mediating through functional health status.