Hidden yet quantifiable: A lower bound for confounding strength using randomized trials

arXiv:2312.03871v2 Announce Type: replace-cross
Abstract: In the era of fast-paced precision medicine, observational studies play a major role in properly evaluating new treatments in clinical practice. Yet, unobserved confounding can significantly compromise causal conclusions drawn from non-randomized data. We propose a novel strategy that leverages randomized trials to quantify unobserved confounding. First, we design a statistical test to detect unobserved confounding with strength above a given threshold. Then, we use the test to estimate an asymptotically valid lower bound on …

abstract arxiv clinical confounding cs.lg data hidden major medicine novel practice precision precision medicine role stat.ml strategy studies type