Introduction
Applications of prediction models.Study design for prediction modeling
Statistical Models for Prediction
Overfitting and optimism in prediction models
Choosing between alternative statistical models
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
Evaluation of Clinical Usefulness
Validation of Prediction Models
Presentation formats
Patterns of external validity
Updating for a new setting
Updating for multiple settings
Case study on a prediction of 30-day mortality
Case study on Survival Analysis: prediction of cardiovascular events
Overall lessons and data sets
References.