Bayesian analysis of multi-type recurrent events and dependent termination with nonparametric covariate functions.
| Autor: | Li-An Lin, Sheng Luo, Chen, Bingshu E., Davis, Barry R., Lin, Li-An, Luo, Sheng |
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| Předmět: |
BAYESIAN analysis
NONPARAMETRIC estimation CORONARY heart disease prevention MYOCARDIAL infarction ANALYSIS of covariance STATISTICAL correlation PARAMETER estimation CARDIOVASCULAR disease related mortality CARDIOVASCULAR disease prevention ANTILIPEMIC agents CLINICAL trials COMPUTER simulation HYPERTENSION LONGITUDINAL method MULTIVARIATE analysis NONPARAMETRIC statistics PROBABILITY theory RESEARCH funding STATISTICS SYSTEM analysis DISEASE relapse PROPORTIONAL hazards models STATISTICAL models |
| Zdroj: | Statistical Methods in Medical Research; Dec2017, Vol. 26 Issue 6, p2869-2884, 16p |
| Abstrakt: | 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. [ABSTRACT FROM AUTHOR] |
| Databáze: | Complementary Index |
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