4 papers · 1 filter
A Mathematical Framework for Topological Causal Data Analysis
Hugo Gobato Souto, Ioannis Diamantis
Many modern outcomes, including images, point clouds, networks, and spatial fields, are structured objects for which \(Y^1-Y^0\) may be undefined or scientifically inadequate. We i…
Forests for Differences: Robust Causal Inference Beyond Parametric DiD
Hugo Gobato Souto, Francisco Louzada Neto
This paper introduces the Difference-in-Differences Bayesian Causal Forest (DiD-BCF), a novel non-parametric model addressing key challenges in DiD estimation, such as staggered ad…
Ablation Studies for Novel Treatment Effect Estimation Models
Hugo Gobato Souto, Francisco Louzada
Ablation studies are essential for understanding the contribution of individual components within complex models, yet their application in nonparametric treatment effect estimation…
Beyond Arbitrary Replications: A Principled Approach to Simulation Design in Causal Inference
Hugo Gobato Souto, Francisco Louzada Neto
Evaluation of novel treatment effect estimators frequently relies on simulation studies lacking formal statistical comparisons and using arbitrary numbers of replications (). Th…