Bayesian analysis of multi-type recurrent events and dependent termination with nonparametric covariate functions.

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2017
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Abstract
Multi-type recurrent event data occur frequently in longitudinal studies. Dependent termination may occur when the terminal time is correlated to recurrent event times. In this article, we simultaneously model the multi-type recurrent events and a dependent terminal event, both with nonparametric covariate functions modeled by B-splines. We develop a Bayesian multivariate frailty model to account for the correlation among the dependent termination and various types of recurrent events. Extensive simulation results suggest that misspecifying nonparametric covariate functions may introduce bias in parameter estimation. This method development has been motivated by and applied to the lipid-lowering trial component of the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial.
Reference Key
lin2017bayesianstatistical Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Lin, Li-An;Luo, Sheng;Chen, Bingshu E;Davis, Barry R;
Journal statistical methods in medical research
Year 2017
DOI
10.1177/0962280215613378
URL
Keywords
hypertension markov chain monte carlo recurrent events joint model multivariate frailty model

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