Amy Herring, Duke University

Title: Bayesian Modeling of Transitions in Sexual Orientation Identity, Behaviors, and Attraction from Adolescence to Adulthood
Abstract: Modeling and computation for multivariate longitudinal data have proven challenging, particularly when data contain discrete measurements of different types. Motivated by data on the fluidity of sexuality from adolescence to adulthood, we propose a novel nonparametric approach for mixed-scale longitudinal data. The proposed approach relies on an underlying variable mixture model with time-varying latent factors. We use our approach to address hypotheses in The National Longitudinal Study of Adolescent to Adult Health, which selected participants via stratified random sampling, leading to discrepancies between the sample and population that are further compounded by missing data. Survey weights have been constructed to address these issues, but including them in complex statistical models is challenging. Bias arising from the survey design and nonresponse is addressed. The approach is assessed via simulation and used to answer questions about the associations among sexual orientation identity, behaviors, and attraction in the transition from adolescence to young adulthood.
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