Logistic Regression Models for Ordinal Response Variables

Journal Data

TypeSOURCE_BOOK
PublisherSAGE Publications, Inc.
ISBN-139781412984812
Open LibraryOL38051913W
Total publications1
Coverage period2006 - 2006
LanguageEN

List of Tables and Figures Series Editor's Introduction Acknowledgments 1. Introduction Purpose of This Book Software and Syntax Organization of the Chapters 2. Context: Early Childhood Longitudinal Study Overview of the Early Childhood Longitudinal Study Practical Relevance of Ordinal Outcomes Variables in the Models 3. Background: Logistic Regression Overview of Logistic Regression Assessing Model Fit Interpreting the Model Measures of Association EXAMPLE 3.1: Logistic Regression Comparing Results Across Statistical Programs 4. The Cumulative (Proportional) Odds Model for Ordinal Outcomes Overview of the Cumulative Odds Model EXAMPLE 4.1: Cumulative Odds Model With a Single Explanatory Variable EXAMPLE 4.2: Full-Model Analysis of Cumulative Odds Assumption of Proportional Odds and Linearity in the Logit Alternatives to the Cumulative Odds Model EXAMPLE 4.3: Partial Proportional Odds 5. The Continuation Ratio Model Overview of the Continuation Ratio Model Link Functions Probabilities of Interest Directionality of Responses and Formation of the Continuation Ratios EXAMPLE 5.1: Continuation Ratio Model With Logit Link and Restructuring the Data EXAMPLE 5.2: 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: Full-Model Continuation Ratio Analyses for the ECLS-K Data 6. The Adjacent Categories Model Overview of the Adjacent Categories Model EXAMPLE 6.1: Gender-Only Model EXAMPLE 6.2: Adjacent Categories Model With Two Explanatory Variables EXAMPLE 6.3: Full Adjacent Categories Model Analysis 7. Conclusion Considerations for Further Study Notes Appendix A: Chapter 3 Appendix B: Chapter 4 Appendix C: Chapter 5 Appendix D: Chapter 6 References Index About the Author