Table of Contents

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   Book Overview
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   Chapter 1 Introduction
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   Chapter 2 Applications of prediction models
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   Chapter 3 Study design for prediction models
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   Chapter 4 Statistical Models for Prediction
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   Chapter 5 Overfitting and optimism in prediction models
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   Chapter 6 Choosing between alternative statistical models
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   Chapter 7 Dealing with missing values
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   Chapter 8 Case study on dealing with missing values
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    Chapter 9 Coding of Categorical and Continuous Predictors
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    Chapter 10 Restrictions on candidate predictors
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    Chapter 11 Selection of main effects
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    Chapter 12 Assumptions in regression models:Additivity and linearity
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    Chapter 13 Modern estimation methods
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    Chapter 14 Estimation with external information
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    Chapter 15 Evaluation of performance
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    Chapter 16 Clinical Usefulness
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    Chapter 17 Validation of Prediction Models
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    Chapter 18 Presentation formats
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    Chapter 19 Patterns of external validity
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    Chapter 20 Updating for a new setting
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    Chapter 21 Updating for multiple settings
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    Chapter 22 Prediction of a binary outcome:30-day mortality after acute myocardial infarction
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    Chapter 23 Case study on survival analysis:prediction of secondary cardiovascular events
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    Chapter 24 Lessons from case studies