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stat.ME2026
Causal inference for group-contaminated structured outcomes: observable quotients, lossless reduction and exact randomization inference
Usef Faghihi, Amir Saki
Structured potential outcomes such as microscopy images may be recorded after an unknown, unit-specific transformation. If that transformation can depend on treatment, covariates o…
stat.ME2026
Topological Ignorability for Structural Causal Effects Beyond Means
Usef Faghihi
Many interventions alter the structure of an outcome distribution rather than its mean: they can split a population into disconnected regimes, create loops or holes, generate branc…
stat.ME2026
Beyond Means: Topological Causal Effects under Persistent-Homology Ignorability
Amir Saki, Usef Faghihi
Average treatment effects (ATE) and conditional average treatment effects (CATE) are foundational causal estimands, but they target changes in expected outcomes and can miss treatm…