35 citations · 104 across the 15 of their papers we have counts for
10 papers · 1 filter
Compatibility of Missing Data Handling Methods across the Stages of Producing Clinical Prediction Models
Antonia Tsvetanova, Matthew Sperrin, David A. Jenkins +7
Missing data is a challenge when developing, validating and deploying clinical prediction models (CPMs). Traditionally, decisions concerning missing data handling during CPM develo…
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…
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…
Imputation and Missing Indicators for handling missing data in the development and implementation of clinical prediction models: a simulation study
Rose Sisk, Matthew Sperrin, Niels Peek +2
Background: Existing guidelines for handling missing data are generally not consistent with the goals of prediction modelling, where missing data can occur at any stage of the mode…
A scoping review of causal methods enabling predictions under hypothetical interventions
Lijing Lin, Matthew Sperrin, David A. Jenkins +2
Background and Aims: The methods with which prediction models are usually developed mean that neither the parameters nor the predictions should be interpreted causally. However, wh…