Departmental Colloquia: Amy Herring

AMY HERRING amy herring

 

Associate Chair, Department of Biostatistics
University of North Carolina, Chapel Hill

 

“Bayesian Models for Multivariate Dynamic Survey Data”

 

ABSTRACT

Modeling and computation for multivariate longitudinal data have proven challenging, particularly when data contain discrete measurements of different types.  The National Longitudinal Study of Adolescent to Adult Health 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.  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.  Bias arising  from the survey design and nonresponse is addressed using an MCMC algorithm.  The approach is assessed via simulation and used to address questions about the association among sexual orientation identity, behaviors, and attraction over time.