The calibrated model-based concordance improved assessment of discriminative ability in patient clusters of limited sample size

The calibrated model-based concordance improved assessment of discriminative ability in patient clusters of limited sample size

Abstract Background Discriminative ability is an important aspect of prediction model performance, but challenging to assess in clustered (e.g., multicenter) data. Concordance (c)-indexes may be too extreme within small clusters. We aimed to define a new approach for the assessment of discriminative...

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Bibliographic Details
Main Authors: David van Klaveren, Ewout W. Steyerberg, Mithat Gönen, Yvonne Vergouwe
Format: Article
Language:English
Published: BMC 2019-06-01
Series:Diagnostic and Prognostic Research
Subjects:
Prediction model
Model performance
Discrimination
Concordance
Clustered data
Multilevel regression
Online Access:http://link.springer.com/article/10.1186/s41512-019-0055-8

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http://link.springer.com/article/10.1186/s41512-019-0055-8

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