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Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating
Presents practical illustrations of how advanced statistical concepts can be applied in prognostic medical research. This book offers a practical checklist with seven steps that need to be considered for development of a valid prediction model.
528 pages, Kindle Edition
First published October 10, 2008
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December 24, 2018
A practical statistical book for clinical prediction model. This book is very easy to read and learn as each chapter very well and in-depth explained " How to develop an effective prediction model, and how to validated the development model by different approaches".
The author described the majority of validation techniques such internal validation (Apparent, Split-sample and bootstrapping), external validation by using another sample that should be similar to the researcher development model predictors. Overall, I recommended this book for those who are interesting to learn or develop a prediction model even in different multi-disciplines as business, social sciences and economics.
The author described the majority of validation techniques such internal validation (Apparent, Split-sample and bootstrapping), external validation by using another sample that should be similar to the researcher development model predictors. Overall, I recommended this book for those who are interesting to learn or develop a prediction model even in different multi-disciplines as business, social sciences and economics.
Displaying 1 of 1 review