Collins, Gary S. and Ogundimu, Emmanuel O. and Altman, Douglas G. (2016) 'Sample size considerations for the external validation of a multivariable prognostic model: a resampling study.', Statistics in Medicine, 35 (2). pp. 214-226.
Abstract
After developing a prognostic model, it is essential to evaluate the performance of the model in samples independent from those used to develop the model, which is often referred to as external validation. However, despite its importance, very little is known about the sample size requirements for conducting an external validation. Using a large real data set and resampling methods, we investigate the impact of sample size on the performance of six published prognostic models. Focussing on unbiased and precise estimation of performance measures (e.g. the c-index, D statistic and calibration), we provide guidance on sample size for investigators designing an external validation study. Our study suggests that externally validating a prognostic model requires a minimum of 100 events and ideally 200 (or more) events
| Item Type: | Article |
|---|---|
| Full text: | (VoR) Version of Record Available under License - Creative Commons Attribution 4.0. Download PDF (2174Kb) |
| Status: | Peer-reviewed |
| Publisher Web site: | https://doi.org/10.1002/sim.6787 |
| Publisher statement: | © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
| Date accepted: | 12 October 2015 |
| Date deposited: | 15 October 2021 |
| Date of first online publication: | 09 November 2015 |
| Date first made open access: | 15 October 2021 |
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