Abstract

Abstract In this article, we provide an overview on the Cox proportional hazards model. We discuss the partial likelihood approach for parameter estimation and inference. Some practical issues in using the Cox regression model are discussed, including how to handle tied data, incorporate time‐dependent covariates, and fit the Cox regression model in stratified population. The article also reviews some practical ways for assessing proportional hazards assumption; one authentic example is used to illustrate data analysis using the Cox regression model. Finally, we list a few extensions of the Cox regression model.

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