You are here

Resources to help you transition to teaching online

Instructors: To support your transition to online learning, please see our resources and tools page whether you are teaching in the UK, or teaching outside of the UK.

Inspection copy update April 2020: Due to the current restrictions in place in response to COVID-19, our inspection copy policy has changed. Please refer to our updated inspection copy policy for full details. If you have recently placed an inspection copy order with us, we will be in touch to advise of any changes.

The Association Graph and the Multigraph for Loglinear Models
Share

The Association Graph and the Multigraph for Loglinear Models



March 2011 | 136 pages | SAGE Publications, Inc
Though the graphical model was introduced in 1980, most of the research and application of the methodology in this field has been done by Europeans. The U.S. has lagged somewhat behind; only in recent years has the graphical model appeared in some of the American textbooks on categorical data, and even then the coverage is limited. The purpose of this work is to provide an initial source of reading for someone interested in the topic.

This publication distinguishs itself from any other book by including the multigraph representation of LLMs, a natural and very effective extension of the graphical model approach. The book's coverage would extend from the LLM, already covered by Knoke and Burke's SAGE publication, "Log-Linear Models," through the development and application of the multigraph representation in one coherent, comprehensive treatment.

 
About the Author
 
Series Editor's Introduction
 
Chapter 1. Introduction
 
Chapter 2. Structures of Association
 
Chapter 3. Loglinear Model Review
 
Chapter 4. Association Graphs for Loglinear Models
 
Chapter 5. Collapsibility Conditions and the Association Graph
 
Chapter 6. The Generator Multigraph
 
Chapter 7. Fundamental Conditional Independencies for Nondecomposable Loglinear Models
 
Chapter 8. Conclusions and Additional Examples
 
Data Sets
 
References
 
Author Index
 
Subject Index

Preview this book

Select a Purchasing Option

SAGE Knowledge is the ultimate social sciences digital library for students, researchers, and faculty. Hosting more than 4,400 titles, it includes an expansive range of SAGE eBook and eReference content, including scholarly monographs, reference works, handbooks, series, professional development titles, and more.

The platform allows researchers to cross-search and seamlessly access a wide breadth of must-have SAGE book and reference content from one source.

SAGE Knowledge brings together high-quality content from across our imprints, including CQ Press and Corwin titles.