Bayesian latent structure modeling of walking behavior in a physical activity intervention

Andrew B. Lawson, Caitlyn Ellerbe, Rachel Carroll, Kassandra Alia, Sandra Coulon, Dawn K. Wilson, M. Lee Vanhorn, Sara M.St George

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

The analysis of walking behavior in a physical activity intervention is considered. A Bayesian latent structure modeling approach is proposed whereby the ability and willingness of participants is modeled via latent effects. The dropout process is jointly modeled via a linked survival model. Computational issues are addressed via posterior sampling and a simulated evaluation of the longitudinal model's ability to recover latent structure and predictor effects is considered. We evaluate the effect of a variety of socio-psychological and spatial neighborhood predictors on the propensity to walk and the estimation of latent ability and willingness in the full study.

Original languageEnglish (US)
Pages (from-to)2634-2649
Number of pages16
JournalStatistical Methods in Medical Research
Volume25
Issue number6
DOIs
StatePublished - Dec 1 2016

Keywords

  • Bayesian
  • Latent structure
  • intervention
  • joint model
  • longitudinal data
  • physical activity

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability
  • Health Information Management

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