• Corpus ID: 251224027

Bias Formulas for Violations of Proximal Identification Assumptions

  title={Bias Formulas for Violations of Proximal Identification Assumptions},
  author={Raluca Cobzaru and Roy E. Welsch and Stan N. Finkelstein and Kenney Ng and Zach Shahn},
Causal inference from observational data often rests on the unverifiable assumption of no unmeasured confounding. Recently, Tchetgen Tchetgen and colleagues have introduced proximal inference to leverage negative control outcomes and exposures as proxies to adjust for bias from unmeasured confounding [16]. However, some of the key assumptions that proximal inference relies on are themselves empirically untestable. Additionally, the impact of violations of proximal inference assumptions on the… 

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