The Annals of Applied Statistics

Longitudinal Mixed Membership trajectory models for disability survey data

Daniel Manrique-Vallier

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Abstract

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.

Article information

Source
Ann. Appl. Stat. Volume 8, Number 4 (2014), 2268-2291.

Dates
First available in Project Euclid: 19 December 2014

Permanent link to this document
https://projecteuclid.org/euclid.aoas/1419001743

Digital Object Identifier
doi:10.1214/14-AOAS769

Mathematical Reviews number (MathSciNet)
MR3292497

Zentralblatt MATH identifier
06408778

Keywords
NLTCS Mixed Membership trajectories multivariate analysis MCMC cohort analysis

Citation

Manrique-Vallier, Daniel. Longitudinal Mixed Membership trajectory models for disability survey data. Ann. Appl. Stat. 8 (2014), no. 4, 2268--2291. doi:10.1214/14-AOAS769. https://projecteuclid.org/euclid.aoas/1419001743.


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Supplemental materials

  • Supplementary material: Supplement to “Longitudinal Mixed Membership trajectory models for disability survey data”. Estimation using TGoM models with piecewise constant trajectories and tables with posterior estimates for all the fitted models.