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SENSIMATCH: Stata module to provide data-driven sensitivity analysis for Matching estimator


  • Giovanni Cerulli

    () (IRCrES-CNR)

Programming Language



sensimatch provides a sensitivity test for checking the robustness of the selection-on-observables assumption in treatment effect observational studies, both within a regression adjustment and a propensity-score matching approach. Rooted in the machine learning literature, this sensitivity analysis is based on a "leave-one-covariate-out" (LOCO) approach. This method recalls a bootstrap over different subsets of covariates, and simulates various estimation scenarios to be compared with the baseline results obtained by the analyst. The main output of sensimatch is graphical, thus providing the user with an easy-to-interpret robustness check of his/her study results.

Suggested Citation

  • Giovanni Cerulli, 2018. "SENSIMATCH: Stata module to provide data-driven sensitivity analysis for Matching estimator," Statistical Software Components S458539, Boston College Department of Economics, revised 20 Jun 2019.
  • Handle: RePEc:boc:bocode:s458539
    Note: This module should be installed from within Stata by typing "ssc install sensimatch". 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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