activity
20242026
collaborators

7 papers

stat.AP2026

MCAnalysis: An Open-Source Package for Preprocessing, Modelling, and Visualisation of Menstrual Cycle Effects in Digital Health Data

Kyra Delray, Glyn Lewis, Bola Grace +2

The menstrual cycle influences numerous physiological and psychological outcomes, yet standardised, open-source statistical methods for quantifying these cyclic effects remain lack…

stat.ME2026

Data Fusion with Distributional Equivalence Test-then-pool

Linying Yang, Xing Liu, Robin J. Evans

Randomized controlled trials (RCTs) are the gold standard for causal inference, yet practical constraints often limit the size of the concurrent control arm. Borrowing control data…

stat.ME2025

Frugal, Flexible, Faithful: Causal Data Simulation via Frengression

Linying Yang, Robin J. Evans, Jens Magelund Tarp +1

Machine learning has revitalized causal inference by combining flexible models and principled estimators, yet robust benchmarking and evaluation remain challenging with real-world…

cs.LG2025

Testing Generalizability in Causal Inference

Daniel de Vassimon Manela, Linying Yang, Robin J. Evans

Ensuring robust model performance in diverse real-world scenarios requires addressing generalizability across domains with covariate shifts. However, no formal procedure exists for…

stat.ME2025

Exact Simulation of Longitudinal Data from Marginal Structural Models

Xi Lin, Daniel de Vassimon Manela, Chase Mathis +2

Simulating longitudinal data from specified marginal structural models is a crucial but challenging task for evaluating causal inference methods and informing study design. While d…

stat.ME2025

Outcome-Informed Weighting for Robust ATE Estimation

Linying Yang, Robin J. Evans

Reliable causal effect estimation from observational data requires adjustment for confounding and sufficient overlap in covariate distributions between treatment groups. However, i…