On semiparametric transformation cure models

• 成果类型: Article
• 署名作者: Lu, WB; Ying, ZL
• 署名单位: Columbia University
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/91.2.331
• 发表日期: 2004
• 页码: 331343
• 关键词: proportional hazards; mixture-models; regression; sample

摘要

A general class of semiparametric transformation cure models is studied for the analysis of survival data with long-term survivors. It combines a logistic regression for the probability of event occurrence with the class of transformation models for the time of occurrence. Included as special cases are the proportional hazards cure model (Farewell, 1982; Kuk Chen, 1992; Sy Taylor, 2000; Peng & Dear, 2000) and the proportional odds cure model. Generalised estimating equations are proposed for parameter estimation. It is shown that the resulting estimators are asymptotically normal, with variance-covariance matrix that has a closed form and can be consistently estimated by the usual plug-in method. Simulation studies show that the proposed approach is appropriate for practical use. An application to data from a breast cancer study is given to illustrate the methodology.