On the accelerated failure time model for current status and interval censored data

• 成果类型: Article
• 署名作者: Tian, Lu; Cai, Tianxi
• 署名单位: Northwestern University; Harvard University
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/93.2.329
• 发表日期: 2006
• 页码: 329342
• 关键词: PROPORTIONAL HAZARDS MODEL; rank-based inference; linear-regression; efficient estimation; odds regression

摘要

This paper introduces a novel approach to making inference about the regression parameters in the accelerated failure time model for current status and interval censored data. The estimator is constructed by inverting a Wald-type test for testing a null proportional hazards model. A numerically efficient Markov chain Monte Carlo based resampling method is proposed for obtaining simultaneously the point estimator and a consistent estimator of its variance-covariance matrix. We illustrate our approach with interval censored datasets from two clinical studies. Extensive numerical studies are conducted to evaluate the finite-sample performance of the new estimators.