Journal
INTERNATIONAL JOURNAL OF BIOSTATISTICS
Volume 15, Issue 2, Pages -Publisher
WALTER DE GRUYTER GMBH
DOI: 10.1515/ijb-2018-0028
Keywords
Berkson error; classical error; instrumental variable; proportional hazards model; simulation extrapolation
Funding
- National Institute of Health [R01ES017030, HL121347, GM100573]
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Many biomedical or epidemiological studies often aim to assess the association between the time to an event of interest and some covariates under the Cox proportional hazards model. However, a problem is that the covariate data routinely involve measurement error, which may be of classical type, Berkson type or a combination of both types. The issue of Cox regression with error-prone covariates has been well-discussed in the statistical literature, which has focused mainly on classical error so far. This paper considers Cox regression analysis when some covariates are possibly contaminated with a mixture of Berkson and classical errors. We propose a simulation extrapolation-based method to address this problem when two replicates of the mismeasured covariates are available along with calibration data for some subjects in a subsample only. The proposed method places no assumption on the mixture percentage. Its finite-sample performance is assessed through a simulation study. It is applied to the analysis of data from an AIDS clinical trial study.
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