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

Hallucination

书目名称Clinical Prediction Models影响因子(影响力)




书目名称Clinical Prediction Models影响因子(影响力)学科排名




书目名称Clinical Prediction Models网络公开度




书目名称Clinical Prediction Models网络公开度学科排名




书目名称Clinical Prediction Models被引频次




书目名称Clinical Prediction Models被引频次学科排名




书目名称Clinical Prediction Models年度引用




书目名称Clinical Prediction Models年度引用学科排名




书目名称Clinical Prediction Models读者反馈




书目名称Clinical Prediction Models读者反馈学科排名

BLAZE

Statistical Models for Prediction,on the most relevant aspects of these models in a prediction context. All models are illustrated with case studies. In Chap. 6, we will discuss aspects of choosing between alternative statistical models.

dictator

Cardioversion

Assumptions in regression models:Additivity and linearity,egies to extend a prediction model with interactions and non-linear terms, since better fulfillment of assumptions in a particular sample does not necessarily imply better predictive performance for future subjects. We consider several case studies for illustration of various strategies to deal with additivity and linearity.

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Book 20091st editionin the medical field with the increase in knowledge on potential predictors of outcome, e.g. from genetics. Also, the number of applications will increase, e.g. with targeted early detection of disease, and individualized approaches to diagnostic testing and treatment. The current era of evidence-ba

Pantry

Pantry

Evaluation of performance,lly relevant for prediction of binary outcomes in individual patients. We will illustrate the use of performance measures in the testicular cancer case study, with model development in 544 patients, internal validation with bootstrapping, and external validation with 273 patients from another centre.

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EWE

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Restrictions on candidate predictors,predictors, combining similar variables, and averaging the effects of similar variables. We provide a detailed description of a case study of modelling similar effects of aspects of family history for robust prediction of the presence of a genetic mutation.