Graphical log-linear models: Fundamental concepts and applications

Article Type

Research Article

Publication Title

Journal of Modern Applied Statistical Methods

Abstract

A comprehensive study of graphical log-linear models for contingency tables is presented. High-dimensional contingency tables arise in many areas. Analysis of contingency tables involving several factors or categorical variables is very hard. To determine interactions among various factors, graphical and decomposable log-linear models are preferred. Connections between the conditional independence in probability and graphs are explored, followed with illustrations to describe how graphical log-linear model are useful to interpret the conditional independences between factors. The problem of estimation and model selection in decomposable models is discussed.

First Page

545

Last Page

577

DOI

10.22237/jmasm/1493598000

Publication Date

1-1-2017

Comments

Open Access, Bronze, Green

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