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Logistic Regression Models for Ordinal Response Variables

ISBN-10: 0761929894
ISBN-13: 9780761929895
Edition: 2006
Authors: Ann A. O'Connell
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Description: Logistic Regression Models for Ordinal Response Variables provides applied researchers in the social, educational, and behavioral sciences with an accessible and comprehensive coverage of analyses for ordinal outcomes. The content builds on a  More...

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Book details

Copyright year: 2006
Publisher: SAGE Publications, Incorporated
Publication date: 11/2/2005
Binding: Paperback
Pages: 120
Size: 5.50" wide x 8.50" long x 0.25" tall
Weight: 0.286
Language: English

Logistic Regression Models for Ordinal Response Variables provides applied researchers in the social, educational, and behavioral sciences with an accessible and comprehensive coverage of analyses for ordinal outcomes. The content builds on a review of logistic regression, and extends to details of the cumulative (proportional) odds, continuation ratio, and adjacent category models for ordinal data. Description and examples of partial proportional odds models are also provided. This book is highly readable, with lots of examples and in-depth explanations and interpretations of model characteristics. SPSS and SAS are used for all examples; data and syntax are available from the author's website. The examples are drawn from an educational context, but applications to other fields of inquiry are noted, such as HIV prevention, behavior change, counseling psychology, social psychology, etc.).  The level of the book is set for applied researchers who need to quickly understand the use and application of these kinds of ordinal regression models.

List of Tables and Figures
Series Editor's Introduction
Acknowledgments
Introduction
Purpose of This Book
Software and Syntax
Organization of the Chapters
Context: Early Childhood Longitudinal Study
Overview of the Early Childhood Longitudinal Study
Practical Relevance of Ordinal Outcomes
Variables in the Models
Background: Logistic Regression
Overview of Logistic Regression
Assessing Model Fit
Interpreting the Model
Measures of Association
Logistic Regression
Comparing Results Across Statistical Programs
The Cumulative (Proportional) Odds Model for Ordinal Outcomes
Overview of the Cumulative Odds Model
Cumulative Odds Model With a Single Explanatory Variable
Full-Model Analysis of Cumulative Odds
Assumption of Proportional Odds and Linearity in the Logit
Alternatives to the Cumulative Odds Model
Partial Proportional Odds
The Continuation Ratio Model
Overview of the Continuation Ratio Model
Link Functions
Probabilities of Interest
Directionality of Responses and Formation of the Continuation Ratios
Continuation Ratio Model With Logit Link and Restructuring the Data
Continuation Ratio Model With Complementary Log-Log Link
Choice of Link and Equivalence of Two Clog-Log Models
Choice of Approach for Continuation Ratio Models
Example 5.3
The Adjacent Categories Model
Overview of the Adjacent Categories Model
Gender-Only Model
Adjacent Categories Model With Two Explanatory Variables
Full Adjacent Categories Model Analysis
Conclusion
Considerations for Further Study
Notes
Chapter 3
Chapter 4
Chapter 5
Chapter 6
References
Index
About the Author

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