Clinical Prediction Models

Springer, series Statistics for Biology and Health

Table of contents


Part I
1. Introduction
2. Applications of prediction models
3. Study design for prediction models
4. Statistical models for prediction
5. Overfitting and optimism in prediction models
6. Choosing between alternative statistical models

Part II
7. Dealing with 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 methods
15. Evaluation of performance
16. Clinical usefulness
17. Validation of prediction models
18. Presentation formats

Part III
19. Patterns of external validity
20. Updating for a new setting
21. Updating for multiple settings

Part IV
22. Prediction of a binary outcome: 30-day mortality after acute myocardial infarction
23. Case study on survival analysis: Prediction of secondary cardiovascular events
24. Lessons from case studies


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