Related Experiment Video
Updated: Jul 19, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Bayesian analysis of paired survival data using a bivariate exponential distribution
Jaeyong Lee1, Jinseog Kim, Sin-Ho Jung
1Department of Statistics, Seoul National University, Sillimdong Kwanakgu, Seoul 151-742, Korea. leej@stats.snu.ac.kr
Abstract:
We consider a Bayesian analysis method of paired survival data using a bivariate exponential model proposed by Moran (1967, Biometrika 54:385-394). Important features of Moran's model include that the marginal distributions are exponential and the range of the correlation coefficient is between 0 and 1. These contrast with the popular exponential model with gamma frailty. Despite these nice properties, statistical analysis with Moran's model has been hampered by lack of a closed form likelihood function. In this paper, we introduce a latent variable to circumvent the difficulty in the Bayesian computation. We also consider a model checking procedure using the predictive Bayesian P-value.
Related Concept Videos
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
Kaplan-Meier Approach
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time until a...
Comparing the Survival Analysis of Two or More Groups
Survival Curves
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...

