14 citations · 39 across the 7 of their papers we have counts for
5 papers · 1 filter
Sequential sample size calculations and learning curves safeguard the robust development of a clinical prediction model for individuals
Amardeep Legha, Joie Ensor, Rebecca Whittle +7
When prospectively developing a new clinical prediction model (CPM), fixed sample size calculations are typically conducted before data collection based on sensible assumptions. Bu…
Clustered Flexible Calibration Plots For Binary Outcomes Using Random Effects Modeling
Lasai Barreñada, Bavo D. C. Campo, Laure Wynants +1
Evaluation of clinical prediction models across multiple clusters, whether centers or datasets, is becoming increasingly common. A comprehensive evaluation includes an assessment o…
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…
Minimum Sample Size for Developing a Multivariable Prediction Model using Multinomial Logistic Regression
Alexander Pate, Richard D Riley, Gary S Collins +4
Multinomial logistic regression models allow one to predict the risk of a categorical outcome with more than 2 categories. When developing such a model, researchers should ensure t…
The harm of class imbalance corrections for risk prediction models: illustration and simulation using logistic regression
Ruben van den Goorbergh, Maarten van Smeden, Dirk Timmerman +1
Methods to correct class imbalance, i.e. imbalance between the frequency of outcome events and non-events, are receiving increasing interest for developing prediction models. We ex…