activity
20242026
collaborators

14 papers

stat.AP2026

Value-of-Information Analysis for External Validation of Risk Prediction Models in Multicenter Studies and Systematic Reviews

Laure Wynants, Kim Zhipei Wang, Sabine Grimm +5

External validation studies have finite sample sizes, creating uncertainty about whether a prediction model's Net Benefit (NB) exceeds default strategies' NB. The expected value of…

stat.ME2026

Progression to the mean: A comparison of Bayesian clinical prediction models outputting the posterior mean versus conventional plug-in predictions

Mohsen Sadatsafavi, Richard D. Riley

Clinical prediction models provide predictions for individuals, typically expressed as point estimates derived from a deterministic function, such as a logistic regression equation…

cs.CY2026

What Medicine Taught Us About Fairness and What It Missed: Lessons from Reconsidering Race-Specific Lung Function Reference Algorithms

Amin Adibi, Mohsen Sadatsafavi

Since 2019, medical societies have reconsidered race-specific clinical equations often in parallel to and largely independent from algorithmic fairness research. Focusing on lung f…

stat.ME2025

Non-parametric assessment of the calibration of individualized treatment effects

Mohsen Sadatsafavi, Jeroen Hoogland, Thomas P. A. Debray +1

An important aspect of the performance of algorithms that predict individualized treatment effects (ITE) is moderate calibration, i.e., the average treatment effect among individua…

stat.AP2025

Transportability of Prognostic Markers: Rethinking Common Practices through a Sufficient-Component-Cause Perspective

Mohsen Sadatsafavi, Gavin Pereira, Wenjia Chen

Transportability, the ability to maintain performance across populations, is a desirable property of markers of clinical outcomes. However, empirical findings indicate that markers…

stat.ME2025

Evaluating Treatment Benefit Predictors using Observational Data: Contending with Identification and Confounding Bias

Yuan Xia, Mohsen Sadatsafavi, Paul Gustafson

A treatment benefit predictor (TBP) is a function that maps patient characteristics to an estimate of the treatment benefit for that patient. Such predictors support optimizing ind…