Transcription of Cox Proportional-Hazards Regression for Survival Data in R
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Cox Proportional-Hazards Regression for Survival Data in R
Cox Proportional-Hazards Regression for Survival Data inRAn Appendix toAn R Companion to Applied Regression , third editionJohn Fox & Sanford Weisberglast revision: 2018-09-28 AbstractSurvival analysisexamines and models the time it takes for events to occur, termedsurvivaltime. TheCox Proportional-Hazards Regression modelis the most common tool for studying thedependency of Survival time on predictor variables. This appendix to Fox and Weisberg (2019)briefly describes the basis for the Cox Regression model , and explains how to use thesurvivalpackage inRto estimate Cox IntroductionSurvival analysisexamines and models the time it takes for events to occur. The prototypical suchevent is death, from which the name Survival analysis and much of its terminology derives, but theambit of application of Survival analysis is much broader. Essentially the same methods are employedin a variety of disciplines under various rubrics for example, event-history analysis in sociologyand failure-time analysis in engineering.
The Cox proportional-hazards regression model is the most common tool for studying the dependency of survival time on predictor variables. This appendix to Fox and Weisberg (2019) brie y describes the basis for the Cox regression model, and explains how to use the survival
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