Non‐proportional odds multivariate logistic regression of ordinal family data

DOI10.1002/bimj.201300137zbMath1310.62121OpenAlexW1929245108WikidataQ35306068 ScholiaQ35306068MaRDI QIDQ5247914

Stephen Harrap, Katrina Scurrah, Lyle C. Gurrin, Justine A. Ellis, Sophie Zaloumis

Publication date: 27 April 2015

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

Full work available at URL: https://doi.org/10.1002/bimj.201300137

zbMATH Keywords

data augmentationMCMC algorithmnon-proportional oddspartially collapsed Gibbs samplingcorrelated ordinal outcomes

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Applications of statistics to social sciences (62P25)

Related Items (1)

Bayesian analysis of Turkish Income and Living Conditions data, using clustered longitudinal ordinal modelling with Bridge distributed random effects

Uses Software

• R
• Stata
• SAS
• GLLAMM
• SAS/STAT

Cites Work

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• Properties of prior and posterior distributions for multivariate categorical response data models
• Models for discrete longitudinal data.
• Univariate and multirater ordinal cumulative link regression with covariate specific cutpoints
• Bayesian Multivariate Logistic Regression
• Partially Collapsed Gibbs Samplers
• Analysis of multivariate probit models
• Interpreting Parameters in the Logistic Regression Model with Random Effects
• A MULTIVARIATE NORMAL MODEL FOR PEDIGREE AND LONGITUDINAL DATA AND THE SOFTWARE ‘FISHER’
• Biometrical Modeling of Twin and Family Data Using Standard Mixed Model Software

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