Bayesian Proportional Odds Models for Analyzing Current Status Data: Univariate, Clustered, and Multivariate

DOI10.1080/03610918.2011.566971zbMath1227.62015OpenAlexW2065234813MaRDI QIDQ3102870

Lianming Wang, Xiaoyan Lin

Publication date: 25 November 2011

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2011.566971

zbMATH Keywords

clustered datamultivariate survival analysismonotone spline

Mathematics Subject Classification ID

Censored data models (62N01) Bayesian inference (62F15)

Related Items (10)

Regression analysis of bivariate current status data under the gamma-frailty proportional hazards model using the EM algorithm ⋮ Spatial extended hazard model with application to prostate cancer survival ⋮ ICBayes: a package of Bayesian semiparametric regression for intervel-censored data ⋮ An EM algorithm for analyzing right-censored survival data under the semiparametric proportional odds model ⋮ Goodness-of-fit inference for the additive hazards regression model with clustered current status data ⋮ Global rates of convergence of the MLE for multivariate interval censoring ⋮ Bayesian Spatial Survival Models ⋮ A Gamma-frailty proportional hazards model for bivariate interval-censored data ⋮ A Unified Framework for Fitting Bayesian Semiparametric Models to Arbitrarily Censored Survival Data, Including Spatially Referenced Data ⋮ A Bayesian proportional hazards model for general interval-censored data

Cites Work

• Bayesian analysis of generalized odds-rate hazards models for survival data
• Generalized additive models for current status data
• Bayesian proportional hazards model for current status data with monotone splines
• Semiparametric proportional odds models for spatially correlated survival data
• Proportional odds regression and sieve maximum likelihood estimation
• Adaptive Rejection Metropolis Sampling within Gibbs Sampling
• Using Conditional Logistic Regression to Fit Proportional Odds Models to Interval Censored Data
• Adaptive Rejection Sampling for Gibbs Sampling
• Bayesian Semiparametric Proportional Odds Models
• Bayesian Inferences on Predictors of Conception Probabilities

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