294 citations · 1.2k across the 73 of their papers we have counts for
7 papers · 1 filter
Robust inference on population indirect causal effects: the generalized front-door criterion
Isabel R. Fulcher, Ilya Shpitser, Stella Marealle +1
Standard methods for inference about direct and indirect effects require stringent no unmeasured confounding assumptions which often fail to hold in practice, particularly in obser…
Semiparametric Causal Sufficient Dimension Reduction Of Multidimensional Treatments
Razieh Nabi, Todd McNutt, Ilya Shpitser
Cause-effect relationships are typically evaluated by comparing outcome responses to binary treatment values, representing two arms of a hypothetical randomized controlled trial. H…
Personalizing Path-Specific Effects
Ilya Shpitser, Sourjya Sarkar
Unlike classical causal inference, which often has an average causal effect of a treatment within a population as a target, in settings such as personalized medicine, the goal is t…
Auto-G-Computation of Causal Effects on a Network
Eric J. Tchetgen Tchetgen, Isabel Fulcher, Ilya Shpitser
Methods for inferring average causal effects have traditionally relied on two key assumptions: (i) the intervention received by one unit cannot causally influence the outcome of an…
Modeling Interference Via Symmetric Treatment Decomposition
Ilya Shpitser, Chan Park, Eric Tchetgen Tchetgen +1
Classical causal inference assumes treatments meant for a given unit do not have an effect on other units. This assumption is violated in interference problems, where new types of…
Fair Inference On Outcomes
Razieh Nabi, Ilya Shpitser
In this paper, we consider the problem of fair statistical inference involving outcome variables. Examples include classification and regression problems, and estimating treatment…