Logistic Regression
eBook - PDF

Logistic Regression

From Introductory to Advanced Concepts and Applications

  1. 393 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Logistic Regression

From Introductory to Advanced Concepts and Applications

About this book

In this text, author Scott Menard provides coverage of not only the basic logistic regression model but also advanced topics found in no other logistic regression text. The book keeps mathematical notation to a minimum, making it accessible to those with more limited statistics backgrounds, while including advanced topics of interest to more statistically sophisticated readers. Not dependent on any one software package, the book discusses limitations to existing software packages and ways to overcome them.

Key FeaturesĀ Ā Ā 

  • Examines the logistic regression model in detail
  • Illustrates concepts with applied examples to help readers understand how concepts are translated into the logistic regression modelĀ 
  • Helps readers make decisions about the criteria for evaluating logistic regression models through detailed coverage of how to assess overall models and individual predictors for categorical dependent variablesĀ 
  • Offers unique coverage of path analysis with logistic regression that shows readers how to examine both direct and indirect effects using logistic regression analysisĀ 
  • Applies logistic regression analysis to longitudinal panel data, helping students understand the issues in measuring change with dichotomous, nominal, and ordinal dependent variables
  • Shows readers how multilevel change models with logistic regression are different from multilevel growth curve models for continuous interval or ratio-scaled dependent variables

Logistic Regression is intended for courses such as Regression and Correlation, Intermediate/Advanced Statistics, and Quantitative Methods taught in departments throughout the behavioral, health, mathematical, and social sciences, including applied mathematics/statistics, biostatistics, criminology/criminal justice, education, political science, public health/epidemiology, psychology, and sociology.

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Yes, you can access Logistic Regression by Scott Menard in PDF and/or ePUB format, as well as other popular books in Social Sciences & Social Science Research & Methodology. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Contents
  3. Preface
  4. About the Author
  5. Chapter 1 - Introduction: Linear Regression and Logistic Regression
  6. Chapter 2 - Log-Linear Analysis, Logit Analysis, and Logistic Regression
  7. Chapter 3 - Quantitative Approaches to Model Fit and Explained Variation
  8. Chapter 4 - Prediction Tables and Qualitative Approaches to Explained Variation
  9. Chapter 5 - Logistic Regression Coefficients
  10. Chapter 6 - Model Specification, Variable Selection, and Model Building
  11. Chapter 7 - Logistic Regression Diagnostics and Problems of Inference
  12. Chapter 8 - Path Analysis With Logistic Regression (PALR)
  13. Chapter 9 - Polytomous Logistic Regression for Unordered Categorical Variables
  14. Chapter 10 - Ordinal Logistic Regression
  15. Chapter 11 - Clusters, Contexts, and Dependent Data: Logistic Regression for Clustered Sample Survey Data
  16. Chapter 12 - Conditional Logistic Regression Models for Related Samples
  17. Chapter 13 - Longitudinal Panel Analysis With Logistic Regression
  18. Chapter 14 - Logistic Regression for Historical and Developmental Change Models: Multilevel Logistic Regression and Discrete Time Event History Analysis
  19. Chapter 15 - Comparisons: Logistic Regression and Alternative Models
  20. Appendix A: Estimation for Logistic Regression Models
  21. Appendix B: Proofs Related to Indices of Predictive Efficiency
  22. Appendix C: Ordinal Measures of Explained Variation
  23. References
  24. Author Index
  25. Subject Index