A semiparametric approach to simultaneous covariance estimation for bivariate sparse longitudinal data

DOI10.1111/biom.12133zbMath1419.62334OpenAlexW2119763274WikidataQ30728550 ScholiaQ30728550MaRDI QIDQ4979224

Kiranmoy Das, Michael J. Daniels

Publication date: 17 June 2014

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc3954444

zbMATH Keywords

covariance matrixMCMCDICDirichlet process mixture of normals

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Generalized linear models (logistic models) (62J12)

Related Items (8)

A semi-parametric Bayesian dynamic hurdle model with an application to the health and retirement study ⋮ Functional mapping of multiple dynamic traits ⋮ A joint quantile regression model for multiple longitudinal outcomes ⋮ Joint penalized spline modeling of multivariate longitudinal data, with application to HIV‐1 RNA load levels and CD4 cell counts ⋮ A semiparametric Bayesian approach for joint modeling of longitudinal trait and event time ⋮ A Bayesian quantile regression approach to multivariate semi-continuous longitudinal data ⋮ A Bayesian approach of analysing semi-continuous longitudinal data with monotone missingness ⋮ Modeling Multiple Time-Varying Related Groups: A Dynamic Hierarchical Bayesian Approach With an Application to the Health and Retirement Study

Uses Software

• MIXED
• SemiPar

Cites Work

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