Bayesian gamma frailty models for survival data with semi-competing risks and treatment switching
From MaRDI portal
Publication:746532
DOI10.1007/s10985-013-9254-8zbMath1322.62114OpenAlexW2092999558WikidataQ30609818 ScholiaQ30609818MaRDI QIDQ746532
Donglin Zeng, Joseph G. Ibrahim, Yuanye Zhang, Xiaodong Xue, Zhiying Pan, Ming-Hui Chen, Qingxia Chen
Publication date: 16 October 2015
Published in: Lifetime Data Analysis (Search for Journal in Brave)
Full work available at URL: http://europepmc.org/articles/pmc3745804
Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Reliability and life testing (62N05)
Related Items
A dependent Dirichlet process model for survival data with competing risks, Frailty modelling approaches for semi-competing risks data, A Bayesian multi‐risks survival (MRS) model in the presence of double censorings, Hazards regression for freemium products and services: a competing risks approach, Bayesian path specific frailty models for multi-state survival data with applications
Cites Work
- Unnamed Item
- Bayesian analysis of generalized odds-rate hazards models for survival data
- Monte Carlo methods in Bayesian computation
- On semi-competing risks data
- Estimating treatment effects with treatment switching via semicompeting risks models: an application to a colorectal cancer study
- The competing risks illness–death model under cross-sectional sampling
- Bivariate Survival Models Induced by Frailties
- The Collapsed Gibbs Sampler in Bayesian Computations with Applications to a Gene Regulation Problem
- Adaption of bivariate frailty models for prediction, with application to biological markers as prognostic indicators
- Propriety of posterior distribution for dichotomous quantal response models
- Bayesian Measures of Model Complexity and Fit
- Estimating the Association Parameter for Copula Models Under Dependent Censoring
- Adaptive Rejection Sampling for Gibbs Sampling
- Regression Modeling of Semicompeting Risks Data
- Statistical models based on counting processes
- Bayesian survival analysis
