Bayesian joint modeling of high-dimensional discrete multivariate longitudinal data using generalized linear mixed models
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Publication:6616386
DOI10.1214/24-aoas1883MaRDI QIDQ6616386
Ronald C. Chen, Joseph G. Ibrahim, XianMing Tan, Paloma Hauser, Fang Chen
Publication date: 9 October 2024
Published in: The Annals of Applied Statistics (Search for Journal in Brave)
longitudinal dataMarkov chain Monte Carlogeneralized linear mixed modelshigh-dimensionalpatient-reported outcomeslow-Rank approximation
Cites Work
- Unnamed Item
- Random-Effects Models for Longitudinal Data
- Statistical analysis of factor models of high dimension
- Optimal scaling for partially updating MCMC algorithms
- Models for discrete longitudinal data.
- Sparse Bayesian infinite factor models
- Sparse Pairwise Likelihood Estimation for Multivariate Longitudinal Mixed Models
- Pairwise estimation of multivariate longitudinal outcomes in a Bayesian setting with extensions to the joint model
- Mixed Effects Models with Bivariate and Univariate Association Parameters for Longitudinal Bivariate Binary Response Data
- Bayesian Measures of Model Complexity and Fit
- Approximate Inference in Generalized Linear Mixed Models
- Bayesian Generalized Low Rank Regression Models for Neuroimaging Phenotypes and Genetic Markers
- Marginalized transition random effect models for multivariate longitudinal binary data
- The analysis of repeated multivariate binary quality of life data: a hierarchical model approach
- Pairwise Fitting of Mixed Models for the Joint Modeling of Multivariate Longitudinal Profiles
- Reduced Rank Stochastic Regression with a Sparse Singular value Decomposition
- Linear mixed models for longitudinal data
- Bayesian generalized linear low rank regression models for the detection of vaccine-adverse event associations
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