Accelerated Failure Time Models with Auxiliary Covariates

Journal of Biometrics & Biostatistics

article

KevinGranville¹  ZhaozhiFan¹ 

[1] Department of Mathematics and Statistics, Memorial University

关键词: Kernel smoothing;    Estimated likelihood function;    Accelerated failure time models;    Measurement errors;    Auxiliary covariates;   

DOI  :  10.4172/2155-6180.1000152

来源: Hilaris Publisher

【 摘 要 】

In this paper we study semi-parametric inference procedure for accelerated failure time models with auxiliary information about a main exposure variable. We use a kernel smoothing method to introduce the auxiliary covariate to the likelihood function. The regression parameters are then estimated through maximization of the estimated likelihood function. A consistent estimator of the variance of the estimator of the regression coefficients is proposed. Simulation studies show that the efficiency gain is remarkable when compared to just using the validation sample. The method is applied to the PBC data from the Mayo Clinic trial in primary biliary cirrhosis as an illustration.

【 授权许可】

Unknown