Generalized method of moments estimation for linear regression with clustered failure time data

• 成果类型: Article
• 署名作者: Li, Hui; Yin, Guosheng
• 署名单位: Beijing Normal University; University of Texas System; UTMD Anderson Cancer Center
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/asp005
• 发表日期: 2009
• 页码: 293306
• 关键词: estimating equations; censored-data; longitudinal data; sample properties; resampling method; rank-tests; restrictions; inference; models

摘要

We propose a generalized method of moments approach to the accelerated failure time model with correlated survival data. We study the semiparametric rank estimator using martingale-based moments. We circumvent direct estimation of correlation parameters by concatenating the moments and minimizing a quadratic objective function. We establish the consistency and asymptotic normality of the parameter estimators, and derive the limiting distribution of the objective function. We carry out simulation studies to examine the finite-sample properties of the method, and demonstrate its substantial efficiency gain over the conventional method. Finally, we illustrate the new proposal with an example from a diabetic retinopathy study.