External validation is necessary in prediction research: a clinical example.

By S. Bleeker, Henriëtte A. Moll, Ewout W. Steyerberg, A. Donders, G. Derksen‐Lubsen, Diederick E. Grobbee, Karel G. M. Moons. Journal of Clinical Epidemiology, 2003

709 citations recorded by the source corpus.

Subfields: Critical Care and Intensive Care Medicine, Epidemiology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/179c254ef9ca53a9933b422681c549e49a34db77

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Critical Care and Intensive Care Medicine

1. Douglas G. Altman

In Epidemiology

1. Karel G. M. Moons
2. Douglas G. Altman
3. Ewout W. Steyerberg
4. R. Riley
5. Gary S. Collins
6. Chava L. Ramspek
7. Kitty J. Jager
8. F. Dekker

In Statistics and Probability

1. Karel G. M. Moons
2. Douglas G. Altman
3. R. Riley
4. Ewout W. Steyerberg
5. Gary S. Collins
6. J. Hayden
7. F. Dekker
8. Kitty J. Jager

Citations in the corpus

• External validation of prognostic models: what, why, how, when and where? (2020, background): “In a large enough dataset, internal validation can give an indication of the model’s external performance [20].”
• Practitioner’s Guide to Latent Class Analysis: Methodological Considerations and Common Pitfalls. (2020, positive): “A key component to demonstrating the validity of classes or subgroups identified using algorithms such as LCA is to demonstrate their reproducibility in external datasets (59, 60).”
• Prognosis Research Strategy (PROGRESS) 3: Prognostic Model Research (2013, methodology): “The predictive performance of a model estimated on the development data is often optimistic, related to multiple testing with a limited sample size [3,5,30,31].”