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NONPARMDE: Stata module to calculate the minimum detectable effect in randomized experiment


  • Joel Middleton

    () (New York University)

  • John Ternovski

    () (Analyst Institute)


nonparmde is a method for calculating the minimum detectable effect (MDE) using the nonparametric estimators proposed in Middleton & Aronow (2011). This program is for use on cluster-level data to calculate the minimum effect that a cluster randomized experiment would be able to reliably detect at a given level of statistical power.

Suggested Citation

  • Joel Middleton & John Ternovski, 2012. "NONPARMDE: Stata module to calculate the minimum detectable effect in randomized experiment," Statistical Software Components S457566, Boston College Department of Economics.
  • Handle: RePEc:boc:bocode:s457566
    Note: This module should be installed from within Stata by typing "ssc install nonparmde". 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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