Open Access
December 2014 Longitudinal Mixed Membership trajectory models for disability survey data
Daniel Manrique-Vallier
Ann. Appl. Stat. 8(4): 2268-2291 (December 2014). DOI: 10.1214/14-AOAS769


We develop methods for analyzing discrete multivariate longitudinal data and apply them to functional disability data on the U.S. elderly population from the National Long Term Care Survey (NLTCS), 1982–2004. Our models build on a Mixed Membership framework, in which individuals are allowed multiple membership on a set of extreme profiles characterized by time-dependent trajectories of progression into disability. We also develop an extension that allows us to incorporate birth-cohort effects, in order to assess inter-generational changes. Applying these methods, we find that most individuals follow trajectories that imply a late onset of disability, and that younger cohorts tend to develop disabilities at a later stage in life compared to their elders.


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Daniel Manrique-Vallier. "Longitudinal Mixed Membership trajectory models for disability survey data." Ann. Appl. Stat. 8 (4) 2268 - 2291, December 2014.


Published: December 2014
First available in Project Euclid: 19 December 2014

zbMATH: 06408778
MathSciNet: MR3292497
Digital Object Identifier: 10.1214/14-AOAS769

Keywords: cohort analysis , MCMC , Mixed membership , Multivariate analysis , NLTCS , Trajectories

Rights: Copyright © 2014 Institute of Mathematical Statistics

Vol.8 • No. 4 • December 2014
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