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Math @ Duke
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Publications [#386849] of Henry Pfister
Papers Published
- Assaad, S; Zeng, S; Pfister, H; Li, F; Carin, L, Hölder Bounds for Sensitivity Analysis in Causal Reasoning
(July, 2021)
(last updated on 2026/02/08)
Abstract: We examine interval estimation of the effect of a treatment T on an outcome Y
given the existence of an unobserved confounder U. Using H\"older's inequality,
we derive a set of bounds on the confounding bias |E[Y|T=t]-E[Y|do(T=t)]| based
on the degree of unmeasured confounding (i.e., the strength of the connection
U->T, and the strength of U->Y). These bounds are tight either when U is
independent of T or when U is independent of Y given T (when there is no
unobserved confounding). We focus on a special case of this bound depending on
the total variation distance between the distributions p(U) and p(U|T=t), as
well as the maximum (over all possible values of U) deviation of the
conditional expected outcome E[Y|U=u,T=t] from the average expected outcome
E[Y|T=t]. We discuss possible calibration strategies for this bound to get
interval estimates for treatment effects, and experimentally validate the bound
using synthetic and semi-synthetic datasets.
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dept@math.duke.edu
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