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Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating (Statistics for Biology and Health) by Ewout W. Steyerberg is a Mathematics article available to read on EtoBox.

What is Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating (Statistics for Biology and Health) about?

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 innovations are insufficiently applied in medical research. Old-fashioned, data hungry methods are often used in data sets of limited size, validation of predictions is not done or done simplistically, and updating of previously developed models is not considered. A sensible strategy is needed for model development, validation, and updating, such that prediction models can better support medical practice. Clinical prediction models presents a practical checklist with seven steps that need to be considered for development of a valid prediction model. These include preliminary considerations such as dealing with missing values; coding of predictors; selection of main effects and interactions for a multivariable model; estimation of model parameters with shrinkage methods and incorporation of external data; evaluation of performance and usefulness; internal validation; and presentation forma

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Author

Ewout W. Steyerberg

Publisher

Springer New York

Published

2009

Language

EN

ISBN

9780387772431

Field

Mathematics (Physical Sciences)