Bayesian Inferences for Panel Count Data and Interval-Censored Data with Nonparametric Modeling of the Baseline Functions

DOI10.1007/978-3-030-88658-5_14OpenAlexW4289357611MaRDI QIDQ5051101

Lu Wang, Lianming Wang, Xiaoyan Lin

Publication date: 18 November 2022

Published in: Emerging Topics in Statistics and Biostatistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-030-88658-5_14

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Reliability and life testing (62N05)

Uses Software

• icenReg

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Two likelihood-based semiparametric estimation methods for panel count data with covariates
• A Bayesian approach for analyzing case 2 interval-censored data under the semiparametric proportional odds model
• Covariates and random effects in a Gamma process model with application to degradation and failure
• A Bayesian proportional hazards model for general interval-censored data
• Survival in dynamic environments
• Bayesian nonparametric estimation based on censored data
• Semiparametric regression analysis of panel count data allowing for within-subject correlation
• Joint analysis of interval-censored failure time data and panel count data
• Efficient estimation for the proportional hazards model with interval censoring
• Tailfree and neutral random probabilities and their posterior distributions
• Two estimators of the mean of a counting process with panel count data.
• Regression analysis of interval-censored failure time data with time-dependent covariates
• A Bayesian approach for semiparametric regression analysis of panel count data
• A flexible, computationally efficient method for fitting the proportional hazards model to interval-censored data
• Spline-based semiparametric projected generalized estimating equation method for panel count data
• A Spline-Based Semiparametric Maximum Likelihood Estimation Method for the Cox Model with Interval-Censored Data
• Hazard Regression for Interval-Censored Data with Penalized Spline
• A semiparametric likelihood-based method for regression analysis of mixed panel-count data
• The Gamma‐Frailty Poisson Model for the Nonparametric Estimation of Panel Count Data
• A Bayesian Approach for the Analysis of Panel‐Count Data with Dependent Termination
• Bayesian inference of hidden gamma wear process model for survival data with ties
• Nonparametric estimation of the shape function in a Gamma process for degradation data
• A Semiparametric Model for Regression Analysis of Interval-Censored Failure Time Data
• Rank-based inference in the proportional hazards model for interval censored data
• Proportional odds regression and sieve maximum likelihood estimation
• Sieve Estimation for the Proportional-Odds Failure-Time Regression Model With Interval Censoring
• A Markov Chain Monte Carlo EM Algorithm for Analyzing Interval-Censored Data under the Cox Proportional Hazards Model
• Bayesian Analysis and Model Selection for Interval‐Censored Survival Data
• A Multiple Imputation Approach to Cox Regression with Interval‐Censored Data
• A Proportional Hazards Model for Interval-Censored Failure Time Data
• A spline‐based semiparametric sieve likelihood method for over‐dispersed panel count data

This page was built for publication: Bayesian Inferences for Panel Count Data and Interval-Censored Data with Nonparametric Modeling of the Baseline Functions