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- W2964674200 abstract "Clinical prediction models aim to provide estimates of absolute risk for a diagnostic or prognostic endpoint. Such models may be derived from data from various studies in the context of a meta-analysis. We describe and propose approaches for assessing heterogeneity in predictor effects and predictions arising from models based on data from different sources. These methods are illustrated in a case study with patients suffering from traumatic brain injury, where we aim to predict 6-month mortality based on individual patient data using meta-analytic techniques (15 studies, n = 11 022 patients). The insights into various aspects of heterogeneity are important to develop better models and understand problems with the transportability of absolute risk predictions." @default.
- W2964674200 created "2019-08-13" @default.
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- W2964674200 date "2019-08-02" @default.
- W2964674200 modified "2023-10-13" @default.
- W2964674200 title "Assessment of heterogeneity in an individual participant data meta‐analysis of prediction models: An overview and illustration" @default.
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- W2964674200 doi "https://doi.org/10.1002/sim.8296" @default.
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