Logistic Regression Models for Ordinal Response Variables

Name: Logistic Regression Models for Ordinal Response Variables
Availability: InStock
ISBN: 9780761929895

ISBN-10: 0761929894

ISBN-13: 9780761929895

Edition: 2006

Authors: Ann Aileen Oâ€²Connell

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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 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…

Book details

List price: $42.00
Copyright year: 2006
Publisher: SAGE Publications, Incorporated
Publication date: 11/2/2005
Binding: Paperback
Pages: 120
Size: 5.20" wide x 8.30" long x 0.30" tall
Weight: 0.286
Language: English

Scholarly InterestsStatistical methods, with an emphasis on single and multilevel generalized linear models; evaluation of professional development and health/education programs or interventions, particularly for HIV prevention; secondary analysis of large-scale databases; capacity building for community-based organizations; translation of evidence-based interventions.



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