Semiparametric regression analysis for clustered failure time data

• 成果类型: Article
• 署名作者: Cai, T; Wei, LJ; Wilcox, M
• 署名单位: Harvard University; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/87.4.867
• 发表日期: 2000
• 页码: 867878
• 关键词: transformation models; censored-data; likelihood; hazards

摘要

Inference procedures based on the partial likelihood function for the Cox proportional hazards model have been generalised to the case in which the data consist of a large number of independent small groups of correlated failure time observations (Lee, Wei & Amato, 1992; Liang, Self & Chang, 1993; Cai & Prentice, 1997). However, the Cox model may not fit the data well. A class of linear transformation models, which includes the proportional hazards and odds models as special cases, has been studied extensively for univariate event times. In this paper, statistical methods to analyse such correlated observations are proposed for these models. We use the data from a recent study of the genetic aetiology of alcoholism to illustrate the new procedures for estimation, prediction and model selection.