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The calibrated model-based concordance improved assessment of discriminative ability in patient clusters of limited sample size
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 ability...
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| 出版年: | Diagn Progn Res |
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| 主要な著者: | , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
BioMed Central
2019
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6551913/ https://ncbi.nlm.nih.gov/pubmed/31183411 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s41512-019-0055-8 |
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