Additive hazards regression of current status data with auxiliary covariates

This paper discusses the regression analysis of current status failure time data arising from the additive hazards model with auxiliary covariates. As often occurs in practice, it is impossible or impractical to measure the exact magnitude of covariates for all subjects in a study. To compensate the...

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Bibliographic Details
Published inCommunications in statistics. Theory and methods Vol. 46; no. 21; pp. 10657 - 10671
Main Authors Feng, Yanqin, Dong, Yuan, Li, Yang
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis 02.11.2017
Taylor & Francis Ltd
Subjects
Additive hazards model
Asymptotic properties
auxiliary covariates
current status data
Failure analysis
Hazards
interval-censored data
Mathematical models
Parameter estimation
partial likelihood
Regression analysis
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Summary:This paper discusses the regression analysis of current status failure time data arising from the additive hazards model with auxiliary covariates. As often occurs in practice, it is impossible or impractical to measure the exact magnitude of covariates for all subjects in a study. To compensate the missing information, some auxiliary covariates are utilized instead. We propose two easy-to-implement procedures for estimation of regression parameters by making use of auxiliary information. The asymptotic properties of the resulting estimators are established and extensive numerical studies indicate that both procedures work well in practice.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:0361-0926
1532-415X
DOI:10.1080/03610926.2016.1242737