| Literature DB >> 24741000 |
Andrew B Lawson1, Caitlyn Ellerbe2, Rachel Carroll2, Kassandra Alia3, Sandra Coulon3, Dawn K Wilson3, M Lee VanHorn3, Sara M St George3.
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.Entities:
Keywords: Bayesian; Latent structure; intervention; joint model; longitudinal data; physical activity
Mesh:
Year: 2014 PMID: 24741000 PMCID: PMC5388556 DOI: 10.1177/0962280214529932
Source DB: PubMed Journal: Stat Methods Med Res ISSN: 0962-2802 Impact factor: 3.021