Related Experiment Video
Updated: Aug 16, 2025

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
[Choice and application of time scale selection for Cox proportional hazards regression model in cohort studies]
1School of Public Health, Fudan University, Shanghai 200032, China State Key Laboratory of Oncogene and Related Genes/Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200032, China.
Abstract:
Cox proportional hazards regression model (Cox model) is the most commonly used multivariate approach in time-to-event data analysis. A vital issue in fitting Cox model is choosing the appropriate time scale related to the occurrence of the outcome events. However, few domestic studies have focused on selecting and applying time scales for Cox model in the analysis of cohort study data. This study briefly introduced and compared several time scales in the reports from literature; and used data from the Shanghai Women's Health Study to illustrate the impact of different time scales on data analysis results, using the association between central obesity and the risk of liver cancer as an example. On this basis, several suggestions on selecting time scales in Cox model are proposed to provide a reference for the analysis of cohort study data.
More Related Videos
Related Concept Videos
Assumptions of Survival Analysis
Comparing the Survival Analysis of Two or More Groups
The Mantel-Cox Log-Rank Test
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time...
Censoring Survival Data

