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EVALUE: Stata module for conducting sensitivity analyses for unmeasured confounding in observational studies


  • Ariel Linden

    () (Linden Consulting Group, LLC)

  • Maya B. Mathur

    (Department of Epidemiology, Harvard University)

  • Tyler J. VanderWeele

    (Department of Epidemiology, Harvard University)


evalue performs sensitivity analyses for unmeasured confounding in observational studies using the methodology proposed by VanderWeele and Ding (2017). evalue reports E-values, defined as the minimum strength of association on the risk ratio scale that an unmeasured confounder would need to have with both the treatment and the outcome to fully explain away a specific treatment-outcome association, conditional on the measured covariates. evalue computes E-values for point estimates (and optionally, confidence limits) for several common outcome types, including risk and rate ratios, odds ratios with common or rare outcomes, hazard ratios with common or rare outcomes, standardized mean differences in outcomes, and risk differences. evalue produces identical results to those computed in the EValue package for R and the web-based graphical interface.

Suggested Citation

  • Ariel Linden & Maya B. Mathur & Tyler J. VanderWeele, 2019. "EVALUE: Stata module for conducting sensitivity analyses for unmeasured confounding in observational studies," Statistical Software Components S458592, Boston College Department of Economics, revised 25 Sep 2019.
  • Handle: RePEc:boc:bocode:s458592
    Note: This module should be installed from within Stata by typing "ssc install evalue". The module is made available under terms of the GPL v3 ( Windows users should not attempt to download these files with a web browser.

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