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Semiparametric Regression Models for Repeated Events with Random Effects and Measurement Error

 

作者: Wenxin Jiang,   BruceW. Turnbull,   LarryC. Clark,  

 

期刊: Journal of the American Statistical Association  （Taylor Available online 1999）
卷期: Volume 94, issue 445  

页码: 111-124

 

ISSN:0162-1459

 

年代: 1999

 

DOI:10.1080/01621459.1999.10473828

 

出版商: Taylor & Francis Group

 

关键词: Consistency;Cox model;Estimating equations;Frailty;Measurement error;Omitted covariates;Point process;Poisson regression;Proportional intensities;Robust estimator;Selenium;Skin cancer;Specification analysis;Unobserved heterogeneity;Validation data

 

数据来源: Taylor

 

摘要:

Statistical methodology is presented for the regression analysis of multiple events in the presence of random effects and measurement error. Omitted covariates are modeled as random effects. Our approach to parameter estimation and significance testing is to start with a naive model of semiparametric Poisson process regression, and then to adjust for random effects and any possible covariate measurement error. We illustrate the techniques with data from a randomized clinical trial for the prevention of recurrent skin tumors.

 

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