Clinical Prediction Models

2. Introduction

3. Applications of prediction models

4. Study design for prediction models

5. Statistical Models for Prediction

6. Overfitting and optimism in prediction models

7. Choosing between alternative statistical models

8. Dealing with missing values

9. Case study on dealing with missing values

10. Coding of Categorical and Continuous Predictors

11. Restrictions on candidate predictors

12. Selection of main effects

13. Assumptions in regression models:Additivity and linearity

14. Modern estimation methods

15. Estimation with external information

16. Evaluation of performance

17. Clinical Usefulness

18. Validation of Prediction Models

19. Presentation formats

20. Patterns of external validity

21. Updating for a new setting

22. Updating for a multiple settings

23. Prediction of a binary outcome:30-day mortality after acute myocardial infarction

24. Case study on survival analysis:prediction of secondary cardiovascular events

25. Lessons from case studies

Nyckelord: MATHEMATICS / Probability & Statistics / General MAT029000