Regression Modeling Strategies

With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis

Authors:

ISBN: 978-3-319-19424-0 (Print) 978-3-319-19425-7 (Online)

Table of contents (21 chapters)

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  1. Front Matter

    Pages i-xxv

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    Chapter

    Pages 1-11

    Introduction

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    Chapter

    Pages 13-44

    General Aspects of Fitting Regression Models

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    Chapter

    Pages 45-61

    Missing Data

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    Chapter

    Pages 63-102

    Multivariable Modeling Strategies

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    Chapter

    Pages 103-126

    Describing, Resampling, Validating, and Simplifying the Model

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    Chapter

    Pages 127-142

    R Software

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    Chapter

    Pages 143-160

    Modeling Longitudinal Responses using Generalized Least Squares

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    Chapter

    Pages 161-180

    Case Study in Data Reduction

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    Chapter

    Pages 181-217

    Overview of Maximum Likelihood Estimation

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    Chapter

    Pages 219-274

    Binary Logistic Regression

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    Chapter

    Pages 275-289

    Case Study in Binary Logistic Regression, Model Selection and Approximation: Predicting Cause of Death

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    Chapter

    Pages 291-310

    Logistic Model Case Study 2: Survival of Titanic Passengers

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    Chapter

    Pages 311-325

    Ordinal Logistic Regression

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    Chapter

    Pages 327-358

    Case Study in Ordinal Regression, Data Reduction, and Penalization

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    Chapter

    Pages 359-387

    Regression Models for Continuous Y and Case Study in Ordinal Regression

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    Chapter

    Pages 389-398

    Transform-Both-Sides Regression

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    Chapter

    Pages 399-422

    Introduction to Survival Analysis

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    Chapter

    Pages 423-451

    Parametric Survival Models

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    Chapter

    Pages 453-474

    Case Study in Parametric Survival Modeling and Model Approximation

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    Chapter

    Pages 475-519

    Cox Proportional Hazards Regression Model

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