Ordinal Log-Linear Models
Book Details
Format
Paperback / Softback
Book Series
Quantitative Applications in the Social Sciences
ISBN-10
0803943768
ISBN-13
9780803943766
Publisher
SAGE Publications Inc
Imprint
SAGE Publications Inc
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Dec 6th, 1994
Print length
72 Pages
Weight
118 grams
Dimensions
14.40 x 21.70 x 0.50 cms
Product Classification:
Social research & statisticsProbability & statistics
Ksh 7,400.00
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What log-linear models can social scientists use to examine categorical variables whose attributes may be logically rank-ordered? In this book, the author presents a technique that is often overlooked but highly advantageous when dealing with such ordered variables as social class, political ideology and life satisfaction attitudes. Beginning with an introduction to the concept and measurement of ordinal models and a brief review of nominal log-linear analysis, the book provides a detailed description of the various ordinal models, including row effects, column effects, uniform association and uniform interaction models. Each model is illustrated with data from the National Survey of Families and Households, with which Ishii-Kuntz discusses
Which log-linear models can social scientists use to examine categorical variables whose attributes may be logically rank ordered? Ordinal Log-Linear Models presents a technique that is often overlooked but highly advantageous when dealing with such ordered variables as social class, political ideology, and life satisfaction attitudes. Beginning with an introduction to the concept and measurement of ordinal models, this book provides a detailed description of the various ordinal models, including row effects, column effects, uniform association, and uniform interaction models. Each model is illustrated with data from the National Survey of Families and Households, with which the author discusses the fit of the models, how alternative models compare, and odds ratios. Additionally, statistical computer software packages that can be used to estimate these models are presented.
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