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Robustly estimating heterogeneity in factorial data using Rashomon Partitions
April 3, 2024, 4:42 a.m. | Aparajithan Venkateswaran, Anirudh Sankar, Arun G. Chandrasekhar, Tyler H. McCormick
cs.LG updates on arXiv.org arxiv.org
Abstract: Many statistical analyses, in both observational data and randomized control trials, ask: how does the outcome of interest vary with combinations of observable covariates? How do various drug combinations affect health outcomes, or how does technology adoption depend on incentives and demographics? Our goal is to partition this factorial space into ``pools'' of covariate combinations where the outcome differs across the pools (but not within a pool). Existing approaches (i) search for a single ``optimal'' …
abstract adoption arxiv control cs.lg data demographics drug combinations econ.em health incentives observable stat.co statistical stat.me stat.ml technology type
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