Preface | |
Statistical Models - Social Science | |
Data Craft | |
What is Regression Analysis? | |
Examining Data | |
Transforming Data | |
Linear Models - Least Squares | |
Linear Least-Squares Regression | |
Statistical Inference for Regression | |
Dummy-Variable Regression | |
Analysis of Variance | |
Statistical Theory for Linear Models | |
The Vector Geometry of Linear Models | |
Linear-Model Diagnostics | |
Unusual and Influential Data | |
Diagnosing Non-Normality, Nonconstant Error Variance, and Nonlinearity | |
Collinearity and its Purported Remedies | |
Generalized Linear Models | |
Logit and Probit Models | |
Generalized Linear Models | |
Extending Linear - Generalized Linear Models | |
Time-Series Regression | |
Nonlinear Regression | |
Nonparametric Regression | |
Robust Regression | |
Missing Data in Regression Models | |
Bootstrapping Regression Models | |
Model Selection, Averaging, and Validation | |
A Notation | |
References | |
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