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Time-varying Covariates and Coefficients in Cox Regression Models

Overview
Journal Ann Transl Med
Publisher AME Publishing Company
Date 2018 Jun 30
PMID 29955581
Citations 265
Authors
Zhongheng Zhang
Jaakko Reinikainen
Kazeem Adedayo Adeleke
Marcel E Pieterse
Catharina G M Groothuis-Oudshoorn
Affiliations
Soon will be listed here.
Abstract

Time-varying covariance occurs when a covariate changes over time during the follow-up period. Such variable can be analyzed with the Cox regression model to estimate its effect on survival time. For this it is essential to organize the data in a counting process style. In situations when the proportional hazards assumption of the Cox regression model does not hold, we say that the effect of the covariate is time-varying. The proportional hazards assumption can be tested by examining the residuals of the model. The rejection of the null hypothesis induces the use of time varying coefficient to describe the data. The time varying coefficient can be described with a step function or a parametric time function. This article aims to illustrate how to carry out statistical analyses in the presence of time-varying covariates or coefficients with R.

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