Education and Human Sciences, College of (CEHS)


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A DISSERTATION Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Doctor of Philosophy, Major: Human Sciences (Gerontology), Under the Supervision of Professor Karl Kosloski. Lincoln, Nebraska: December 2012

Copyright (c) 2012 Kuan-Yuan Wang


Objective: The aim of the study is to evaluate the relationship between two dimensions of religiosity, religious service attendance and religious beliefs, and the process of aging, controlling for the effects of covariates known to affect religious development among older adults.

Methods: Secondary analysis of longitudinal data from the Florida Retirement Study was used to assess the trajectories of religious development over time as modeled with two growth processes: religious service attendance and religious beliefs. We analyzed data from six interview waves (Waves 1 and 5 - 9) with 1000 older adults age 72 or over. Covariates included demographic factors (age, gender, marital status, income, education and religious preference), functional disability, and self-rated global health. A latent variable growth model of religious attendance and self-rated religiosity was estimated using Mplus version 6.1.

Results: A baseline model (Model 1) of growth processes only (i.e., without predictor variables) indicated significant variation and mean decline in religious attendance, but no significant variation nor mean change in religious beliefs over time. This initial model also showed significant variation in both religious attendance and religious beliefs at the first wave analyzed. Based on these findings, a second model (Model 1a) was estimated that included an intercept for both latent variables, but included a slope term for religious attendance only. Additionally, to increase parsimony, this second model also constrained the error variances of the indicators for religious attendance to be equal and the error variances of religious beliefs to be equal (Model 2). Finally, a third model (Model 3) was estimated that included the latent variables of model 2 and constrained error variances, plus a set of 17 covariates. The model fit statistics for the final model of religious attendance indicated very good fit for this latent growth curve model.

Conclusion: The decline in mean religious attendance across time did not accompany a mean increase in religious beliefs as expected. There were numerous individual differences in the trajectory of decline for religious attendance, as well as in the initial levels of attendance and religious beliefs.

Adviser: Karl Kosloski