Regression Analysis of Multivariate Interval-Censored Failure Time Data under Transformation Model with Informative Censoring

Mengzhu Yu and Mingyue Du ()
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Mengzhu Yu: School of Mathematics, Jilin University, Changchun 130012, China
Mingyue Du: School of Mathematics, Jilin University, Changchun 130012, China

Mathematics, 2022, vol. 10, issue 18, 1-17

Abstract: We consider a regression analysis of multivariate interval-censored failure time data where the censoring may be informative. To address this, an approximated maximum likelihood estimation approach is proposed under a general class of semiparametric transformation models, and in the method, the frailty approach is employed to characterize the informative interval censoring. For the implementation of the proposed method, we develop a novel EM algorithm and show that the resulting estimators of the regression parameters are consistent and asymptotically normal. To evaluate the empirical performance of the proposed estimation procedure, we conduct a simulation study, and the results indicate that it performs well for the situations considered. In addition, we apply the proposed approach to a set of real data arising from an AIDS study.

Keywords: case K interval-censored data; informative censoring; semiparametric transformation model; sieve approach (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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