A multivariate logistic distance model for the analysis of multiple binary responses

DOI10.1007/s00357-018-9251-4zbMath1391.62146OpenAlexW2790241086MaRDI QIDQ724607

Hailemichael M. Worku, Mark de Rooij

Publication date: 26 July 2018

Published in: Journal of Classification (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00357-018-9251-4

zbMATH Keywords

generalized estimating equationsmarginal modelmultidimensional scalingmultidimensional unfoldingbiplotsmultivariate binary dataclustered bootstrap

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Generalized linear models (logistic models) (62J12)

Uses Software

• R
• SAS
• LISREL
• geepack
• Mmm
• SAS/STAT
• PROC_R

Cites Work

• Longitudinal data analysis using generalized linear models
• Generalized estimating equations.
• Ideal point discriminant analysis revisited with a special emphasis on visualization
• Properties of ideal point classification models for bivariate binary data
• The cluster bootstrap consistency in generalized estimating equations
• Modern multidimensional scaling. Theory and applications.
• Akaike's Information Criterion in Generalized Estimating Equations
• A comparison between bootstrap methods and generalized estimating equations for correlated outcomes in generalized linear models
• Statistical methods for understanding cognitive growth: A review, a synthesis and an application
• Multivariate regression models for discrete and continuous repeated measurements
• The biplot graphic display of matrices with application to principal component analysis
• Longitudinal Data Analysis
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