Identifying Causal Effects With Proxy Variables of an Unmeasured Confounder
Methodology
2018-06-29 v4
Abstract
We consider a causal effect that is confounded by an unobserved variable, but with observed proxy variables of the confounder. We show that, with at least two independent proxy variables satisfying a certain rank condition, the causal effect is nonparametrically identified, even if the measurement error mechanism, i.e., the conditional distribution of the proxies given the con- founder, may not be identified. Our result generalizes the identification strategy of Kuroki & Pearl (2014) that rests on identification of the measurement error mechanism. When only one proxy for the confounder is available, or the required rank condition is not met, we develop a strategy to test the null hypothesis of no causal effect.
Keywords
Cite
@article{arxiv.1609.08816,
title = {Identifying Causal Effects With Proxy Variables of an Unmeasured Confounder},
author = {Wang Miao and Zhi Geng and Eric Tchetgen Tchetgen},
journal= {arXiv preprint arXiv:1609.08816},
year = {2018}
}