On the Regression Analysis of Multivariate Failure Time Data
研究了当个体可能经历多次失效时，如何分析回归效应，提出了两类分层比例风险模型，并推导了偏似然函数。
The paper is concerned with the analysis of regression effects when individual study subjects may experience multiple failures. The proposed methods are most likely to be useful when there are a fairly large number of study subjects. Two general classes of regression models are considered in order to relate the hazard or intensity function to covariates and to preceding failure time history. Both models are of a stratified proportional hazards type. One model includes baseline intensity functions that are arbitrary as a function of time from the beginning of study, while the other includes baseline intensity functions that are arbitrary as a function of time from the study subject's immediately preceding failure. Partial likelihood functions are derived for the regression coefficients. Generalizations and illustrations are given.