Joint modeling of recurrent event processes and intermittently observed time-varying binary covariate processes
From MaRDI portal
Publication:268692
DOI10.1007/S10985-014-9316-6zbMath1356.62211OpenAlexW2076640207WikidataQ41554327 ScholiaQ41554327MaRDI QIDQ268692
Publication date: 15 April 2016
Published in: Lifetime Data Analysis (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/1805/10936
Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Estimation in survival analysis and censored data (62N02)
Related Items (2)
Bayesian Approach for Joint Modeling Longitudinal Data and Survival Data Simultaneously in Public Health Studies ⋮ An efficient estimation approach to joint modeling of longitudinal and survival data
Cites Work
- Unnamed Item
- Unnamed Item
- Cox's regression model for counting processes: A large sample study
- Variational approximations for categorical causal modeling with latent variables
- A Bayesian Semiparametric Joint Hierarchical Model for Longitudinal and Survival Data
- Markov Regression Models for Time Series: A Quasi-Likelihood Approach
- Efficient estimation of semiparametric transformation models for counting processes
- A Joint Model for Longitudinal Measurements and Survival Data in the Presence of Multiple Failure Types
- Covariate measurement errors and parameter estimation in a failure time regression model
- Regression Methods for Poisson Process Data
- Inference and missing data
- Analysis of Censored Survival Data with Intermittently Observed Time-Dependent Binary Covariates
- A Joint Model for Survival and Longitudinal Data Measured with Error
- Jointly Modeling Longitudinal and Event Time Data With Application to Acquired Immunodeficiency Syndrome
- Semiparametric Regression for the Mean and Rate Functions of Recurrent Events
- Bayesian Analysis and Model Selection for Interval‐Censored Survival Data
- A Transitional Model for Longitudinal Binary Data Subject to Nonignorable Missing Data
- Adaptive Rejection Sampling for Gibbs Sampling
- Joint Analysis of Longitudinal Data With Informative Observation Times and a Dependent Terminal Event
- Dynamic Analysis of Recurrent Event Data with Missing Observations, with Application to Infant Diarrhoea in Brazil
- Bayesian Survival Analysis With Nonproportional Hazards
- Joint modelling of longitudinal measurements and event time data
This page was built for publication: Joint modeling of recurrent event processes and intermittently observed time-varying binary covariate processes