Robust joint modeling of longitudinal measurements and time to event data using normal/independent distributions: A Bayesian approach

DOI10.1002/bimj.201200272zbMath1441.62280OpenAlexW1577972884WikidataQ34888788 ScholiaQ34888788MaRDI QIDQ2857992

T. Baghfalaki, Mojtaba Ganjali, Damon M. Berridge

Publication date: 19 November 2013

Published in: Biometrical Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/bimj.201200272

zbMATH Keywords

longitudinal dataMarkov chain Monte CarloBayesian approachnormal/independent distributionsjoint modelsCox's proportional hazard modeltime to event data

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15)

Related Items (3)

Robust Bayesian hierarchical model using normal/independent distributions ⋮ Bayesian variable selection and estimation in semiparametric joint models of multivariate longitudinal and survival data ⋮ A shared parameter model of longitudinal measurements and survival time with heterogeneous random-effects distribution

Uses Software

• WinBUGS
• boa

Cites Work

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