Epidemiology (Cambridge, Mass.)CausalityHumansConfounding FactorsEpidemiologicModels
Bounds and E-values for Marginal Causal Effects.
Arvid Sjölander, Iuliana Ciocănea-Teodorescu, Erin E Gabriel
Published: 202610.1097/EDE.0000000000001919
Abstract
Unmeasured confounding is an important obstacle when estimating causal effects from observational data. Ding and VanderWeele (EPIDEMIOLOGY 2016;27:368) derived bounds for causal effects, based on sensitivity parameters that quantify the maximal stren…
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