Applied ordinal logistic regression using Stata : from single-level to multilevel modeling
Regression analysis Statistics
SAGE Publications, Inc
2016
EISBN 1071878972
Intro.
Half Title.
Publisher Note.
Title Page.
Copyright Page.
Brief Contents.
Detailed Contents.
Acknowledgments.
Preface.
About the Author.
Chapter 1 Stata Basics.
Chapter 2 Review of Basic Statistics.
Chapter 3 Logistic Regression for Binary Data.
Chapter 4 Proportional Odds Models for Ordinal Response Variables.
Chapter 5 Partial Proportional Odds Models and Generalized Ordinal Logistic Regression Models.
Chapter 6 Continuation Ratio Models.
Chapter 7 Adjacent Categories Logistic Regression Models.
Chapter 8 Stereotype Logistic Regression Models.
Chapter 9 Ordinal Logistic Regression With Complex Survey Sampling Designs.
Chapter 10 Multilevel Modeling for Continuous and Binary Response Variables.
Chapter 11 Multilevel Modeling for Ordinal Response Variables.
Chapter 12 Beyond Ordinal Logistic Regression Models: Ordinal Probit Regression Models and Multinomial Logistic Regression Models.
Key Formulas for Statistical Models.
Appendix: List of Stata User-Written Commands.
References.
Index.
The first book to provide a unified framework for both single-level and multilevel modeling of ordinal categorical data, Applied Ordinal Logistic Regression Using Stata helps readers learn how to conduct analyses, interpret the results from Stata output, and present those results in scholarly writing. Using step-by-step instructions, this non-technical, applied book leads students, applied researchers, and practitioners to a deeper understanding of statistical concepts by closely connecting the underlying theories of models with the application of real-world data using statistical software.
Half Title.
Publisher Note.
Title Page.
Copyright Page.
Brief Contents.
Detailed Contents.
Acknowledgments.
Preface.
About the Author.
Chapter 1 Stata Basics.
Chapter 2 Review of Basic Statistics.
Chapter 3 Logistic Regression for Binary Data.
Chapter 4 Proportional Odds Models for Ordinal Response Variables.
Chapter 5 Partial Proportional Odds Models and Generalized Ordinal Logistic Regression Models.
Chapter 6 Continuation Ratio Models.
Chapter 7 Adjacent Categories Logistic Regression Models.
Chapter 8 Stereotype Logistic Regression Models.
Chapter 9 Ordinal Logistic Regression With Complex Survey Sampling Designs.
Chapter 10 Multilevel Modeling for Continuous and Binary Response Variables.
Chapter 11 Multilevel Modeling for Ordinal Response Variables.
Chapter 12 Beyond Ordinal Logistic Regression Models: Ordinal Probit Regression Models and Multinomial Logistic Regression Models.
Key Formulas for Statistical Models.
Appendix: List of Stata User-Written Commands.
References.
Index.
The first book to provide a unified framework for both single-level and multilevel modeling of ordinal categorical data, Applied Ordinal Logistic Regression Using Stata helps readers learn how to conduct analyses, interpret the results from Stata output, and present those results in scholarly writing. Using step-by-step instructions, this non-technical, applied book leads students, applied researchers, and practitioners to a deeper understanding of statistical concepts by closely connecting the underlying theories of models with the application of real-world data using statistical software.
