500 citations
- University of CambridgeGB71 papers
- University College LondonGB12 papers
- Newcastle UniversityGB11 papers
- Imperial College LondonGB8 papers
- The Alan Turing InstituteGB7 papers
- Medical Research CouncilGB6 papers
- Sapienza University of RomeIT6 papers
- Novartis (Switzerland)CH5 papers
- Public Health EnglandGB5 papers
- UK Health Security AgencyGB5 papers
- University of OxfordGB5 papers
- Amsterdam University Medical CentersNL4 papers
5 papers · 1 filter
The Interplay between Bayesian Inference and Conformal Prediction
Nina Deliu, Brunero Liseo
Conformal prediction has emerged as a cutting-edge methodology in statistics and machine learning, providing prediction intervals with finite-sample frequentist coverage guarantees…
On the interplay between prior weight and variance of the robustification component in Robust Mixture Prior Bayesian Dynamic Borrowing approach
Marco Ratta, Gaelle Saint-Hilary, Mauro Gasparini +1
Robust Mixture Prior (RMP) is a popular Bayesian dynamic borrowing method, which combines an informative historical distribution with a less informative component (referred as robu…
Assessing the impact of variance heterogeneity and misspecification in mixed-effects location-scale models
Vincent Jeanselme, Marco Palma, Jessica K Barrett
Linear Mixed Model (LMM) is a common statistical approach to model the relation between exposure and outcome while capturing individual variability through random effects. However,…
A Bayesian location-scale joint model for time-to-event and multivariate longitudinal data with association based on within-individual variability
Marco Palma, Ruth H Keogh, Siobhán B Carr +5
Within-individual variability of health indicators measured over time is becoming commonly used to inform about disease progression. Simple summary statistics (e.g. the standard de…
Revisiting Optimal Allocations for Binary Responses: Insights from Considering Type-I Error Rate Control
Lukas Pin, Sofía S. Villar, William F. Rosenberger
This work revisits optimal response-adaptive designs from a type-I error rate perspective, highlighting when and how much these allocations exacerbate type-I error rate inflation -…