What do we mean by validating a prognostic model?

By Douglas G. Altman, Patrick Royston. Statistics in Medicine, 2000

1,552 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/aa764e1dbd3d2b42215bd907f6dd66b15645bf43

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Citations in the corpus

A new framework to enhance the interpretation of external validation studies of clinical prediction models. (2015, positive): “This framework uses concepts that were previously proposed [6,7,14,15].”
External validation of prognostic models: what, why, how, when and where? (2020, methodology): “courage adjusting the model to better fit the external validation cohort [18, 29, 30].”
Prognosis and prognostic research: validating a prognostic model (2009, background): “In this article, we discuss how to evaluate the performance of a prognostic model in new data.”
Are the Emotions Expressed in Music Genre-specific? An Audio-based Evaluation of Datasets Spanning Classical, Film, Pop and Mixed Genres (2011, background): “The fact that a model is being tested and found accurate across diverse settings, also called transportability, is the most valuable way of establishing external validity for the model (Justice et al, 1999 ), and also the only way to build generalizability into the modelling process (Altman & Roy”
cutpointr: Improved Estimation and Validation of Optimal Cutpoints in R (2020, methodology): “Popular validation methods include training / test splits, k-fold cross-validation, and diﬀerent variations of the bootstrap (Altman and Royston 2000; Arlot and Celisse 2010).”
Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies: The CHARMS Checklist (2014, methodology): “Regardless of the modelling technique, bootstrapping is particularly recommended in small datasets with many candidate predictors and when predictor selection techniques have been used [3,49,51, 55,58,59].”
Why Most Published Research Findings Are False (2005, positive): “Thus, other factors being equal, research findings are more likely true in scientifi c fields that undertake large studies, such as randomized controlled trials in cardiology (several thousand subjects randomized) [14] than in scientifi c fields with small studies, such as most research of molecular”
Diagnosing insulin resistance in the general population. (2001, methodology): “It is well known that scoring systems established in one set of data may not predict as well in a new sample; therefore, using the selected variables, another bootstrap procedure was used to carry out internal validation (15,16).”