195 citations · 381 across the 8 of their papers we have counts for
8 papers
Calibration plots for multistate risk predictions models: an overview and simulation comparing novel approaches
Alexander Pate, Matthew Sperrin, Richard D. Riley +9
Introduction. There is currently no guidance on how to assess the calibration of multistate models used for risk prediction. We introduce several techniques that can be used to pro…
Stability of clinical prediction models developed using statistical or machine learning methods
Richard D Riley, Gary S Collins
Clinical prediction models estimate an individual's risk of a particular health outcome, conditional on their values of multiple predictors. A developed model is a consequence of t…
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…
A tutorial on individualized treatment effect prediction from randomized trials with a binary endpoint
J Hoogland, J IntHout, M Belias +6
Randomized trials typically estimate average relative treatment effects, but decisions on the benefit of a treatment are possibly better informed by more individualized predictions…
A regression-based method for detecting publication bias in multivariate meta-analysis
Chuan Hong, Jing Zhang, Yang Li +3
Publication bias occurs when the publication of research results depends not only on the quality of the research but also on its nature and direction. The consequence is that publi…
Clinical Prediction Models to Predict the Risk of Multiple Binary Outcomes: a comparison of approaches
Glen P. Martin, Matthew Sperrin, Kym I. E. Snell +2
Clinical prediction models (CPMs) are used to predict clinically relevant outcomes or events. Typically, prognostic CPMs are derived to predict the risk of a single future outcome.…