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About Ordinal Log-Linear Models

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 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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  • Language:
  • English
  • ISBN:
  • 9780803943766
  • Binding:
  • Paperback
  • Pages:
  • 72
  • Published:
  • December 5, 1994
  • Dimensions:
  • 217x144x5 mm.
  • Weight:
  • 118 g.
Delivery: 1-2 weeks
Expected delivery: September 28, 2025

Description of Ordinal Log-Linear Models

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 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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