A New Approach for Regression Analysis of Multivariate Current Status Data with Informative Censoring
作者机构：Department of StatisticsYunnan UniversityKunming 650091People’s Republic of China Department of StatisticsUniversity of MissouriColumbiaMO 65211USA
出 版 物：《Communications in Mathematics and Statistics》 (数学与统计通讯（英文）)
年 卷 期：2023年第11卷第4期
页 面：775-794页
核心收录：
学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学]
基 金：supported by Grants from the Natural Science Foundation of China[Grant Number 11731011] a grant from key project of the Yunnan Province Foundation,China[Grant Number 202001BB050049]
主 题：Additive hazards model Current status data Informative censoring
摘 要：Regression analysis of interval-censored failure time data has recently attracted a great deal of attention partly due to their increasing occurrences in many *** this paper,we discuss a type of such data,multivariate current status data,where in addition to the complex interval data structure,one also faces dependent or informative censor*** inference,a sieve maximum likelihood estimation procedure is developed and the proposed estimators of regression parameters are shown to be asymptotically consistent and *** the implementation of the method,an EM algorithm is provided,and the results from an extensive simulation study demonstrate the validity and good performance of the proposed inference *** an illustration,the proposed approach is applied to a tumorigenicity experiment.
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