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Titlebook: Clinical Prediction Models; A Practical Approach Ewout W. Steyerberg Book 20091st edition Springer-Verlag New York 2009 An?sthesie-Informat

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樓主: Hallucination
41#
發(fā)表于 2025-3-28 18:15:33 | 只看該作者
Book 20091st editionand applications of prediction models are often suboptimal in medical publications. With this book Ihope to contribute to better understanding of relevant issues and give practical advice on better modelling strategies than are nowadays widely used. Issues include: (a) Better predictive modelling is
42#
發(fā)表于 2025-3-28 21:37:57 | 只看該作者
Safety in Chemistry Laboratories,imates per centre are drawn towards the average to improve the quality of predictions. We then turn to overfitting in regression models, and discuss the concepts of selection and estimation bias. Again, shrinkage is a solution, which now draws estimated regression coefficients to less extreme values
43#
發(fā)表于 2025-3-28 23:37:02 | 只看該作者
44#
發(fā)表于 2025-3-29 06:57:02 | 只看該作者
45#
發(fā)表于 2025-3-29 08:06:03 | 只看該作者
1431-8776 his book Ihope to contribute to better understanding of relevant issues and give practical advice on better modelling strategies than are nowadays widely used. Issues include: (a) Better predictive modelling is978-0-387-77244-8Series ISSN 1431-8776 Series E-ISSN 2197-5671
46#
發(fā)表于 2025-3-29 11:53:35 | 只看該作者
Overfitting and optimism in prediction models,imates per centre are drawn towards the average to improve the quality of predictions. We then turn to overfitting in regression models, and discuss the concepts of selection and estimation bias. Again, shrinkage is a solution, which now draws estimated regression coefficients to less extreme values
47#
發(fā)表于 2025-3-29 16:34:40 | 只看該作者
48#
發(fā)表于 2025-3-29 20:55:13 | 只看該作者
49#
發(fā)表于 2025-3-30 01:38:09 | 只看該作者
50#
發(fā)表于 2025-3-30 05:56:17 | 只看該作者
Statistical Models for Prediction,urvival data. We discuss common statistical models in medical research such as the linear, logistic, and Cox regression model, and also simpler approaches and more flexible extensions, including regression trees and neural networks. Details of the methods are found in many excellent texts. We focus
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