Logistic Regression Models for Ordinal Response Variables
- Ann A. O'Connell - Ohio State University, USA
Volume:
146
Courses:
Experimental & Quasi-Experimental Research | Intermediate/Advanced Research Methods | Intermediate/Advanced Statistics | Quantitative Methods | Quantitative Methods for Geography | Quantitative Research Methods in Education | Quantitative/Statistical Research in Business & Management | Regression & Correlation | Research Methods & Experimental Psychology | Research Methods in Social Psychology | Statistics in Political Science | Statistics in Psychology
Experimental & Quasi-Experimental Research | Intermediate/Advanced Research Methods | Intermediate/Advanced Statistics | Quantitative Methods | Quantitative Methods for Geography | Quantitative Research Methods in Education | Quantitative/Statistical Research in Business & Management | Regression & Correlation | Research Methods & Experimental Psychology | Research Methods in Social Psychology | Statistics in Political Science | Statistics in Psychology
November 2005 | 120 pages | SAGE Publications, Inc
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
1. Introduction
2. Context: Early Childhood Longitudinal Study
3. Background: Logistic Regression
4. The Cumulative (Proportional) Odds Model for Ordinal Outcomes
5. The Continuation Ratio Model
6. The Adjacent Categories Model
7. Conclusion
Notes
Appendix A: Chapter 3
Appendix B: Chapter 4
Appendix C: Chapter 5
Appendix D: Chapter 6
References
Index
About the Author