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Regression Modeling Strategies

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Cover of 'Regression Modeling Strategies'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 General Aspects of Fitting Regression Models
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    Chapter 3 Missing Data
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    Chapter 4 Multivariable Modeling Strategies
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    Chapter 5 Resampling, Validating, Describing, and Simplifying the Model
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    Chapter 6 S-Plus Software
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    Chapter 7 Case Study in Least Squares Fitting and Interpretation of a Linear Model
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    Chapter 8 Case Study in Imputation and Data Reduction
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    Chapter 9 Overview of Maximum Likelihood Estimation
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    Chapter 10 Binary Logistic Regression
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    Chapter 11 Logistic Model Case Study 1: Predicting Cause of Death
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    Chapter 12 Logistic Model Case Study 2: Survival of Titanic Passengers
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    Chapter 13 Ordinal Logistic Regression
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    Chapter 14 Case Study in Ordinal Regression, Data Reduction, and Penalization
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    Chapter 15 Models Using Nonparametric Transformations of X and Y
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    Chapter 16 Introduction to Survival Analysis
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    Chapter 17 Parametric Survival Models
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    Chapter 18 Case Study in Parametric Survival Modeling and Model Approximation
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    Chapter 19 Cox Proportional Hazards Regression Model
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    Chapter 20 Case Study in Cox Regression
Attention for Chapter 3: Missing Data
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