Efnisyfirlit

• Cover
• Front Matter
• 1. Introduction
• Part I. Prediction Models in Medicine
• 2. Applications of Prediction Models
• 3. Study Design for Prediction Modeling
• 4. Statistical Models for Prediction
• 5. Overfitting and Optimism in Prediction Models
• 6. Choosing Between Alternative Models
• Part II. Developing Valid Prediction Models
• 7. Missing Values
• 8. Case Study on Dealing with Missing Values
• 9. Coding of Categorical and Continuous Predictors
• 10. Restrictions on Candidate Predictors
• 11. Selection of Main Effects
• 12. Assumptions in Regression Models: Additivity and Linearity
• 13. Modern Estimation Methods
• 14. Estimation with External Information
• 15. Evaluation of Performance
• 16. Evaluation of Clinical Usefulness
• 17. Validation of Prediction Models
• 18. Presentation Formats
• Part III. Generalizability of Prediction Models
• 19. Patterns of External Validity
• 20. Updating for a New Setting
• 21. Updating for Multiple Settings
• Part IV. Applications
• 22. Case Study on a Prediction of 30-Day Mortality
• 23. Case Study on Survival Analysis: Prediction of Cardiovascular Events
• 24. Overall Lessons and Data Sets
• Back Matter