Related Experiment Video
Updated: Jul 15, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Bayesian analysis of generalized odds-rate hazards models for survival data
Tathagata Banerjee1, Ming-Hui Chen, Dipak K Dey
1Department of Statistics, Calcutta University, Calcutta, 700019, India. tathagata.bandyopadhyay@gmail.com
Abstract:
In the analysis of censored survival data Cox proportional hazards model (1972) is extremely popular among the practitioners. However, in many real-life situations the proportionality of the hazard ratios does not seem to be an appropriate assumption. To overcome such a problem, we consider a class of nonproportional hazards models known as generalized odds-rate class of regression models. The class is general enough to include several commonly used models, such as proportional hazards model, proportional odds model, and accelerated life time model. The theoretical and computational properties of these models have been re-examined. The propriety of the posterior has been established under some mild conditions. A simulation study is conducted and a detailed analysis of the data from a prostate cancer study is presented to further illustrate the proposed methodology.
Related Concept Videos
Hazard Rate
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...
Assumptions of Survival Analysis
Comparing the Survival Analysis of Two or More Groups
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time until a...
Cancer Survival Analysis
