A semiparametric Bayesian approach for analyzing longitudinal data from multiple related groups

DOI10.1515/ijb-2015-0002MaRDI QIDQ6633140

Lauren Spirko, Prince Afriyie, Kiranmoy Das

Publication date: 5 November 2024

Published in: The International Journal of Biostatistics (Search for Journal in Brave)

zbMATH Keywords

MCMClinear mixed modellongitudinal responsematrix stick-breaking processcholesterol level

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

• Random-Effects Models for Longitudinal Data
• Bayesian estimation and variable selection for single index models
• Joint estimation of mean-covariance model for longitudinal data with basis function approximations
• Nonparametric estimation of mean and covariance structures for longitudinal data
• Missing Data in Longitudinal Studies
• Bayesian Inference in Semiparametric Mixed Models for Longitudinal Data
• The Matrix Stick-Breaking Process
• Semiparametric Regression
• On modelling mean-covariance structures in longitudinal studies
• Joint mean-covariance models with applications to longitudinal data: unconstrained parameterisation
• A semiparametric approach to simultaneous covariance estimation for bivariate sparse longitudinal data
• A nonparametric prior for simultaneous covariance estimation
• Deviance information criteria for missing data models

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