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| Each chapter concludes with Conclusion and Exercises | |
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| Introduction | |
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| A Review of the Linear Regression Model | |
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| Issues of Interest | |
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| How to Estimate a Linear Regression Model | |
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| A Detailed Example of an OLS Regression Model | |
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| The Assumptions of the OLS (Linear) Regression Model | |
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| Interaction Terms in the OLS (Linear) Regression Model | |
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| Introduction to Generalized Linear Models | |
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| The Role of the Link Function | |
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| The Binomial Distribution | |
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| The Multinomial Distribution | |
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| The Poisson Distribution | |
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| The Negative Binomial Distribution | |
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| How Do We Estimate Regression Models Based on These Distributions? How to Check the Significance of Coefficients and the Fit of the Model | |
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| Logistic and Probit Regression Models | |
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| What Are the Alternatives to the Linear Regression Model? Diagnostic Tests for the Logistic Regression Model | |
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| Ordered Logistic and Probit Regression Models | |
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| Alternative Models for Ordinal Dependent Variables | |
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| The Ordered Logistic Regression Model | |
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| Testing the Proportional Odds Assumption | |
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| The Ordered Probit Regression Model | |
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| Introducing Multiple Independent Variables | |
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| The Multinomial Logistic Regression Model | |
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| Introducing Multiple Independent Variables | |
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| Diagnostic Tests for the Multinomial Logistic Regression Model | |
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| Alternatives to the Multinomial Logistic Regression Model | |
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| Poisson and Negative Binomial Regression Models | |
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| The Poisson Regression Model | |
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| The Overdispersed Poisson Regression Model | |
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| The Negative Binomial Regression Model | |
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| Diagnostic Tests for the Poisson Regression Model | |
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| Other Models for Count Variables | |
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| Event History and Survival Models | |
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| Continuous versus Discrete Time Models | |
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| Censoring and Time-Dependent covariates | |
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| The Basics: Survivor and Hazard Functions and Curves | |
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| Parametric Event History Models | |
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| The Cox Proportional Hazards Model | |
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| Where Do We Go from Here? | |
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| Sample Selection | |
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| Endogeneity | |
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| Longitudinal Data | |
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| Multilevel Models | |
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| Nonparametric regression | |
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| Stata, SPSS, and SAS Programs for Examples in Chapters | |
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| References | |