Association Graph and the Multigraph for Loglinear Models

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(136 Seiten)
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ISBN-13:
9781452223421
Einband:
PDF
Seiten:
136
Autor:
Harry J. Khamis
Serie:
Quantitative Applications in the Social Sciences
eBook Typ:
PDF
eBook Format:
PDF
Kopierschutz:
Adobe DRM [Hard-DRM]
Sprache:
Englisch
Beschreibung:

The Association Graph and the Multigraph for Loglinear Models will help students, particularly those studying the analysis of categorical data, to develop the ability to evaluate and unravel even the most complex loglinear models without heavy calculations or statistical software. This supplemental text reviews loglinear models, explains the association graph, and introduces the multigraph to students who may have little prior experience of graphical techniques, but have some familiarity with categorical variable modeling. The author presents logical step-by-step techniques from the point of view of the practitioner, focusing on how the technique is applied to contingency table data and how the results are interpreted.
The Association Graph and the Multigraph for Loglinear Models will help students, particularly those studying the analysis of categorical data, to develop the ability to evaluate and unravel even the most complex loglinear models without heavy calculations or statistical software. This supplemental text reviews loglinear models, explains the association graph, and introduces the multigraph to students who may have little prior experience of graphical techniques, but have some familiarity with categorical variable modeling. The author presents logical step-by-step techniques from the point of view of the practitioner, focusing on how the technique is applied to contingency table data and how the results are interpreted.
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.

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