Table of Contents
Series Editor's Introduction
Preface
1. The Logic of Logistic Regression
Regression with a Dummy Dependent Variable
Transforming Probabilities into Logits
Linearizing the Nonlinear
Summary
2. Interpreting Logistic Regression Coefficients
Logged Odds
Odds
Probabilities
Tests of Significance
Standardized Coefficients
An Example
Summary
3. Estimation and Model Fit
Maximum Likelihood Estimation
Log Likelihood Function
Estimation
Tests of Significance Using Log Likelihood Values
Model Evaluation
An Example
Summary
4. Probit Analysis
Another Way to Linearize the Nonlinear
Probit Analysis
Interpreting the Coefficients
Maximum Likelihood Estimation
An Example
Summary
5. Conclusion
Notes
Appendix: Logarithms
The Logic of Logarithms
Properties of Logarithms
Natural Logarithms
Summary
References
About the Author
Acknowledgments