Bayesian semiparametric joint model of multivariate longitudinal and survival data with dependent censoring
DOI10.1007/s10985-023-09608-5OpenAlexW4385827723MaRDI QIDQ6071450
Dalei Yu, Nian Sheng Tang, An Min Tang
Publication date: 23 November 2023
Published in: Lifetime Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10985-023-09608-5
longitudinal datasurvival datadependent censoringjoint modelpenalized-splines with linear constraints
Applications of statistics to biology and medical sciences; meta analysis (62P10) Censored data models (62N01) Estimation in survival analysis and censored data (62N02) Survival analysis and censored data (62Nxx)
Cites Work
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- Inference using shape-restricted regression splines
- Missing data methods in longitudinal studies: a review
- Maximum likelihood analysis of semicompeting risks data with semiparametric regression models
- An introduction to copulas.
- Joint modeling of longitudinal continuous, longitudinal ordinal, and time-to-event outcomes
- Semiparametric Bayesian joint models of multivariate longitudinal and survival data
- Sieve maximum likelihood estimation for the proportional hazards model under informative censoring
- A parallel evolutionary multiple-try Metropolis Markov chain Monte Carlo algorithm for sampling spatial partitions
- Consistent estimation of a joint model for multivariate longitudinal and survival data with latent variables
- Parallelizing MCMC sampling via space partitioning
- Quantile regression-based Bayesian joint modeling analysis of longitudinal-survival data, with application to an AIDS cohort study
- Jointly modeling longitudinal proportional data and survival times with an application to the quality of life data in a breast cancer trial
- Bayesian variable selection and estimation in semiparametric joint models of multivariate longitudinal and survival data
- Semiparametric maximum likelihood estimation in normal transformation models for bivariate survival data
- Sieve maximum likelihood regression analysis of dependent current status data
- Semiparametric Approaches for Joint Modeling of Longitudinal and Survival Data with Time-Varying Coefficients
- A Joint Model for Longitudinal Measurements and Survival Data in the Presence of Multiple Failure Types
- Regression Survival Analysis with an Assumed Copula for Dependent Censoring: A Sensitivity Analysis Approach
- Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
- General Right Censoring and Its Impact on the Analysis of Survival Data
- A Joint Model for Survival and Longitudinal Data Measured with Error
- Semiparametric Marginal Regression Analysis for Dependent Competing Risks Under an Assumed Copula
- Bayesian Influence Measures for Joint Models for Longitudinal and Survival Data
- Estimates of marginal survival for dependent competing risks based on an assumed copula
- Modelling Progression of CD4-Lymphocyte Count and Its Relationship to Survival Time
- Simultaneous probability statements for Bayesian P-splines
- Equation of State Calculations by Fast Computing Machines
- Joint Models for Multivariate Longitudinal and Multivariate Survival Data
- Monte Carlo sampling methods using Markov chains and their applications
- Joint modelling of longitudinal measurements and event time data
- Semiparametric Normal Transformation Models for Spatially Correlated Survival Data
- Bayesian survival analysis
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