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Updated: Mar 20, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
External model validation of binary clinical risk prediction models in cardiovascular and thoracic surgery
Graeme L Hickey1, Eugene H Blackstone2
1Department of Biostatistics, University of Liverpool, Liverpool, United Kingdom.
Abstract:
Clinical risk-prediction models serve an important role in healthcare. They are used for clinical decision-making and measuring the performance of healthcare providers. To establish confidence in a model, external model validation is imperative. When designing such an external model validation study, thought must be given to patient selection, risk factor and outcome definitions, missing data, and the transparent reporting of the analysis. In addition, there are a number of statistical methods available for external model validation. Execution of a rigorous external validation study rests in proper study design, application of suitable statistical methods, and transparent reporting.
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