Regression modelling of interval censored data based on the adaptive ridge procedure

作     者：Bouaziz, Olivier Lauridsen, Eva Nuel, Gregory 

作者机构：Univ Paris MAP5 UMR CNRS 8145 Paris France Copenhagen Univ Hosp Ressource Ctr Rare Oral Dis Copenhagen Denmark CNRS 7599 LPSM Paris France 

出 版 物：《JOURNAL OF APPLIED STATISTICS》 (应用统计学杂志)

年 卷 期：2022年第49卷第13期

页      面：3319-3343页

核心收录：

学科分类：0202[经济学-应用经济学] 02[经济学] 020208[经济学-统计学] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 

主　　题：Adaptive ridge procedure cure model EM algorithm interval censoring penalised likelihood piecewise constant hazard 

摘      要：A new method for the analysis of time to ankylosis complication on a dataset of replanted teeth is proposed. In this context of left-censored, interval-censored and right-censored data, a Cox model with piecewise constant baseline hazard is introduced. Estimation is carried out with the expectation maximisation (EM) algorithm by treating the true event times as unobserved variables. This estimation procedure is shown to produce a block diagonal Hessian matrix of the baseline parameters. Taking advantage of this interesting feature in the EM algorithm, a L-0 penalised likelihood method is implemented in order to automatically determine the number and locations of the cuts of the baseline hazard. This procedure allows to detect specific areas of time where patients are at greater risks for ankylosis. The method can be directly extended to the inclusion of exact observations and to a cure fraction. Theoretical results are obtained which allow to derive statistical inference of the model parameters from asymptotic likelihood theory. Through simulation studies, the penalisation technique is shown to provide a good fit of the baseline hazard and precise estimations of the resulting regression parameters.