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What is Proportionality Assumption

Chapter 146
Encyclopedia of Data Science and Machine Learning
Proportionality assumption in Cox Regression means that the ratio of the hazards for any two individuals is constant over time. If we don't have proportional hazards, the regression coefficient should be modeled over time and referred to as a time-varying coefficient.
Published in Chapter:
Challenges and Chances of Classical Cox Regression
Mengying Xia (Emory University, USA) and Leigh Wang (Northwestern University, USA)
Copyright: © 2023 |Pages: 12
DOI: 10.4018/978-1-7998-9220-5.ch146
Abstract
Cox regression is the method for investigating the effect of several variables upon the time a specified event takes to happen. It is also known as the proportional hazards regression because it is all revolved around survival analysis. The Cox proportional hazards (CPH) model is the most frequently used approach for survival analysis in a wide variety of fields. This article summarizes current research, especially its applications in the area of diagnosis and treatment of coronavirus disease 2019 (COVID-19). Also, the pros and cons of competitive machine learning (ML) models for targeting the same object will be presented.
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