SIMEX method for censored quantile regression with measurement error

Censored quantile regression serves as an important supplement to the Cox proportional hazards model in survival analysis. In addition to being exposed to censoring, some covariates may subject to measurement error. This leads to substantially biased estimate without taking this error into account....

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Bibliographic Details
Published inCommunications in statistics. Simulation and computation Vol. 46; no. 10; pp. 7552 - 7560
Main Authors Mao, Guangcai, Wei, Yi, Liu, Yanyan
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis 26.11.2017
Taylor & Francis Ltd
Subjects
62 (Statistics)
62N02 (Estimation)
Computer simulation
Economic models
Error analysis
Hazards
Measurement error
Quantile regression
Regression analysis
SIMEX method
Statistical models
Survival analysis
Survival data
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ISSN0361-0918
1532-4141
DOI10.1080/03610918.2016.1242731

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Summary:Censored quantile regression serves as an important supplement to the Cox proportional hazards model in survival analysis. In addition to being exposed to censoring, some covariates may subject to measurement error. This leads to substantially biased estimate without taking this error into account. The SIMulation-EXtrapolation (SIMEX) method is an effective tool to handle the measurement error issue. We extend the SIMEX approach to the censored quantile regression with covariate measurement error. The algorithm is assessed via extensive simulations. A lung cancer study is analyzed to verify the validation of the proposed method.
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ISSN:0361-0918
1532-4141
DOI:10.1080/03610918.2016.1242731