Log-mean linear models for binary data

DOI10.1093/biomet/ass080zbMath1284.62465arXiv1109.6239OpenAlexW2084970779MaRDI QIDQ5411049

Luca La Rocca, Monia Lupparelli, Alberto Roverato

Publication date: 22 April 2014

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1109.6239

zbMATH Keywords

contingency tablesgraphical Markov modelsmarginal independencemean parameters

Mathematics Subject Classification ID

Measures of association (correlation, canonical correlation, etc.) (62H20) Generalized linear models (logistic models) (62J12) Applications of graph theory (05C90)

Related Items (7)

Composite mixture of log-linear models with application to psychiatric studies ⋮ Joint and marginal causal effects for binary non-independent outcomes ⋮ Hierarchical models for independence structures of networks ⋮ A class of smooth models satisfying marginal and context specific conditional independencies ⋮ Context-Specific Independencies Embedded in Chain Graph Models of Type I ⋮ Conjugate and conditional conjugate Bayesian analysis of discrete graphical models of marginal independence ⋮ Log‐mean Linear Parameterization for Discrete Graphical Models of Marginal Independence and the Analysis of Dichotomizations

This page was built for publication: Log-mean linear models for binary data