Regression Modeling Strategies : With Applications to Linear Models, Logistic Regression, and Survival Analysis

Introduction * General Aspects of Fitting Regression Models * Missing Data * Multivariable Modeling Strategies * Resampling, Validating, Describing, and Simplifying the Model * S-PLUS Software * Case Study in Least Squares Fitting and Interpretation of a Linear Model * Case Study in Imputation and Data Reduction * Overview of Maximum Likelihood Estimation * Binary Logistic Regression * Logistic Model Case Study 1: Predicting Cause of Death * Logistic Model Case Study 2: Survival of Titanic Passengers * Ordinal Logistic Regression * Case Study in Ordinal Regrssion, Data Reduction, and Penalization * Models Using Nonparametic Transformations of X and Y * Introduction to Survival Analysis * Parametric Survival Models * Case Study in Parametric Survival Modeling and Model Approximation * Cox Proportional Hazards Regression Model * Case Study in Cox Regression