Joint modeling of multivariate longitudinal mixed measurements and time to event data using a Bayesian approach

DOI10.1080/02664763.2014.898132zbMath1352.62076OpenAlexW2018220320MaRDI QIDQ2953255

T. Baghfalaki, Damon M. Berridge, Mojtaba Ganjali

Publication date: 4 January 2017

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

Full work available at URL: https://doi.org/10.1080/02664763.2014.898132

zbMATH Keywords

conditional predictive ordinateMarkov Chain Monte Carlomultivariate longitudinal datamixed ordinal and continuous responsestime to event data

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Bayesian inference (62F15)

Related Items (6)

A Bayesian conditional model for bivariate mixed ordinal and skew continuous longitudinal responses using quantile regression ⋮ A Bayesian shared parameter model for joint modeling of longitudinal continuous and binary outcomes ⋮ Augmented mixed beta regression models with skew-normal independent distributions: Bayesian analysis of labor force data ⋮ A transition model for analyzing multivariate longitudinal data using Gaussian copula approach ⋮ A shared parameter model of longitudinal measurements and survival time with heterogeneous random-effects distribution ⋮ Bayesian quantile regression for analyzing ordinal longitudinal responses in the presence of non-ignorable missingness

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