Failure Time Models with Matched Data
研究了匹配对数据中比例风险模型的估计方法，提出假设基线风险为独立伽马变量的估计量，在删失数据下比传统方法更有效，且对多种分布假设表现稳健。
Holt & Prentice (1974) adapted the proportional hazards model to give failure time models for matched pairs in which a member of the ith pair with covariate z has hazard function λoi(t) exp(βz). With full data, more efficient estimators of β can be obtained if a Weibull specialization, λintnt–1, of the baseline, hazard can be assumed but these estimators are unavailable for censored data. Estimates of β formed by assuming the λi's are independent gamma variates are investigated. The resulting estimators are found to be more efficient than those obtained by Holt & Prentice when the λi,'s are in fact gamma, to be available for censored data, and to perform well under a number of very different unimodal alternatives to a gamma distribution for the λi 's.