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

Joel Middleton (joel.middleton@gmail.com) and John Ternovski (johnt1@gmail.com)
Additional contact information
Joel Middleton: New York University
John Ternovski: Analyst Institute

Statistical Software Components from Boston College Department of Economics

Abstract: 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.

Language: Stata
Requires: Stata version 11.0 and xvalols (q.v.)
Keywords: minimum detectable effect; clustered data; statistical power (search for similar items in EconPapers)
Date: 2012-12-09
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 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
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Downloads: (external link)
http://fmwww.bc.edu/repec/bocode/n/nonparmde.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/n/nonparmde.sthlp help file (text/plain)
http://fmwww.bc.edu/repec/bocode/n/nonparmde_examples.do sample do-file (text/plain)

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