collaborators

5 papers

stat.ME2026

Deriving Complete Constraints in Hidden Variable Models

Michael C. Sachs, Erin E. Gabriel, Robin J. Evans +1

Hidden variable graphical models can sometimes imply constraints on the observable distribution that are more complex than simple conditional independence relations. These observab…

stat.ME2025

Bounds for causal mediation effects

Marie S. Breum, Vanessa Didelez, Erin E. Gabriel +1

Several frameworks have been proposed for studying causal mediation analysis. What these frameworks have in common is that they all make assumptions for point identifications that…

stat.ME2025

Propensity weighting plus adjustment in proportional hazards model is not doubly robust

Erin E Gabriel, Michael C Sachs, Ingeborg Waernbaum +5

Recently, it has become common for applied works to combine commonly used survival analysis modeling methods, such as the multivariable Cox model and propensity score weighting, wi…

stat.CO2025

Improved small-sample inference for functions of parameters in the k-sample multinomial problem

Michael C Sachs, Erin E Gabriel, Michael P Fay

When the target parameter for inference is a real-valued, continuous function of probabilities in the -sample multinomial problem, variance estimation may be challenging. In sma…

stat.ME2025

Adding covariates to bounds: What is the question?

Gustav Jonzon, Erin E Gabriel, Arvid Sjölander +1

Symbolic nonparametric bounds for partial identification of causal effects now have a long history in the causal literature. Sharp bounds, bounds that use all available information…