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
Avainsanat: MATHEMATICS / Probability & Statistics / General MAT029000
- Julkaisija
- Springer
- Julkaisuvuosi
- 2009
- Kieli
- en
- Painos
- 1
- Kategoria
- Eksaktit luonnontieteet
- Tiedostomuoto
- E-kirja
- eISBN (PDF)
- 9780387772448