Statistical Models for Ordinal Variables
SAGE Publications Inc (Publisher)
1st Edition
Published on 19. April 1994
Book
Hardback
199 pages
978-0-8039-3676-8 (ISBN)
Description
This volume demonstrates how data involving response variables of the many ordered categories can be analyzed, and what techniques would be most useful in analyzing partially ordered variables regarded as dependent variables.
The applications of new models and methods for the analysis of ordinal variables are emphasized and techniques outlined include: general procedures for assessing the goodness-of-fit; review of the independence model and saturated model; defining measures of association; demonstrating the logit versions of the model; and development of association models and logit-type models.
The applications of new models and methods for the analysis of ordinal variables are emphasized and techniques outlined include: general procedures for assessing the goodness-of-fit; review of the independence model and saturated model; defining measures of association; demonstrating the logit versions of the model; and development of association models and logit-type models.
Reviews / Votes
" . . . a fine resource of clear description and explanation of the use of statistical models for ordinal data." -- M.C. Jones * Journal of the Royal Statistical Society *More details
Series
Language
English
Place of publication
Thousand Oaks
United States
Target group
Professional and scholarly
Weight
469 gr
ISBN-13
978-0-8039-3676-8 (9780803936768)
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Schweitzer Classification
Content
Preliminaries
The Linear-by-Linear Interaction Model
Association Models for Two-Way Tables
The ANOAS Approach
Other Models for Two-Way Tables
Symmetry-Type Models
Multiple Dimensions of Association
Bivariate Association in Multiple Groups
Logit-Type Regression Models for Ordinal Dependent Variables
The Linear-by-Linear Interaction Model
Association Models for Two-Way Tables
The ANOAS Approach
Other Models for Two-Way Tables
Symmetry-Type Models
Multiple Dimensions of Association
Bivariate Association in Multiple Groups
Logit-Type Regression Models for Ordinal Dependent Variables