5 papers · 1 filter
The harms of class imbalance corrections for machine learning based prediction models: a simulation study
Alex Carriero, Kim Luijken, Anne de Hond +3
Risk prediction models are increasingly used in healthcare to aid in clinical decision making. In most clinical contexts, model calibration (i.e., assessing the reliability of risk…
The risks of risk assessment: causal blind spots when using prediction models for treatment decisions
Nan van Geloven, Ruth H Keogh, Wouter van Amsterdam +12
Clinicians increasingly rely on prediction models to guide treatment choices. Most prediction models, however, are developed using observational data that include some patients who…
Risk-based decision making: estimands for sequential prediction under interventions
Kim Luijken, Paweł Morzywołek, Wouter van Amsterdam +14
Prediction models are used amongst others to inform medical decisions on interventions. Typically, individuals with high risks of adverse outcomes are advised to undergo an interve…
Replicability of Simulation Studies for the Investigation of Statistical Methods: The RepliSims Project
K. Luijken, A. Lohmann, U. Alter +13
Results of simulation studies evaluating the performance of statistical methods are often considered actionable and thus can have a major impact on the way empirical research is im…
Impact of predictor measurement heterogeneity across settings on performance of prediction models: a measurement error perspective
Kim Luijken, Rolf H. H. Groenwold, Ben van Calster +2
It is widely acknowledged that the predictive performance of clinical prediction models should be studied in patients that were not part of the data in which the model was derived.…