Clinical Prediction Models A Practical Approach to Development, Validation, and Updating /
This book provides insight and practical illustrations on how modern statistical concepts and regression methods can be applied in medical prediction problems, including diagnostic and prognostic outcomes. Many advances have been made in statistical approaches towards outcome prediction, but these i...
| Κύριος συγγραφέας: | |
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| Συγγραφή απο Οργανισμό/Αρχή: | |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
New York, NY :
Springer New York : Imprint: Springer,
2009.
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| Σειρά: | Statistics for Biology and Health,
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| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Applications of prediction models
- Study design for prediction models
- Statistical Models for Prediction
- Overfitting and optimism in prediction models
- Choosing between alternative statistical models
- Dealing with missing values
- Case study on dealing with missing values
- Coding of Categorical and Continuous Predictors
- Restrictions on candidate predictors
- Selection of main effects
- Assumptions in regression models:Additivity and linearity
- Modern estimation methods
- Estimation with external information
- Evaluation of performance
- Clinical Usefulness
- Validation of Prediction Models
- Presentation formats
- Patterns of external validity
- Updating for a new setting
- Updating for multiple settings
- Prediction of a binary outcome:30-day mortality after acute myocardial infarction
- Case study on survival analysis:prediction of secondary cardiovascular events
- Lessons from case studies.
