A semiparametric Bayesian approach for joint modeling of longitudinal trait and event time

DOI10.1080/02664763.2016.1155108OpenAlexW2401214894MaRDI QIDQ5138221

Kiranmoy Das

Publication date: 3 December 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2016.1155108

zbMATH Keywords

proportional hazardsmultiple testingDirichlet process priordistance correlationBayesian Lasso

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items

A semi-parametric Bayesian dynamic hurdle model with an application to the health and retirement study

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Measuring and testing dependence by correlation of distances
• Semiparametric Bayes Multiple Testing: Applications to Tumor Data
• The Bayesian Lasso
• Jointly Modeling Longitudinal and Event Time Data With Application to Acquired Immunodeficiency Syndrome
• Optimal Sample Size for Multiple Testing
• Gibbs Sampling Methods for Stick-Breaking Priors
• Modeling the Relationship of Survival to Longitudinal Data Measured with Error. Applications to Survival and CD4 Counts in Patients with AIDS
• Dirichlet Lasso: A Bayesian approach to variable selection
• A semiparametric approach to simultaneous covariance estimation for bivariate sparse longitudinal data
• Joint Models for Multivariate Longitudinal and Multivariate Survival Data
• Joint modelling of longitudinal measurements and event time data
• Deviance information criteria for missing data models