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 language | English (US) |
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Pages (from-to) | 2634-2649 |
Number of pages | 16 |
Journal | Statistical Methods in Medical Research |
Volume | 25 |
Issue number | 6 |
DOIs | |
State | Published - Dec 1 2016 |
Externally published | Yes |
Keywords
- Bayesian
- Latent structure
- intervention
- joint model
- longitudinal data
- physical activity
ASJC Scopus subject areas
- Epidemiology
- Statistics and Probability
- Health Information Management