3 papers
stat.ME2026
Inference on counterfactual distributions using martingale posteriors
Gregor Steiner, Mark Steel
Causal inference is often focused on average effects, which can hide important aspects of the effect distributions. Here we consider the entire posterior effects distribution by es…
stat.ME2026
Possibilistic Instrumental Variable Regression with Potentially Invalid Instruments
Gregor Steiner, Jeremie Houssineau, Mark F. J. Steel
Instrumental variable regression is a common approach for causal inference in the presence of unobserved confounding. However, identifying valid instruments is often difficult in p…
stat.ME2026
Bayesian Model Averaging in Causal Instrumental Variable Models
Gregor Steiner, Mark Steel
Instrumental variables are a popular tool to infer causal effects under unobserved confounding, but choosing suitable instruments is challenging in practice. We propose gIVBMA, a B…