RANDCMDCI: Stata module to produce robust randomization-t p-values and confidence intervals for regression coefficients

Alwyn Young ()
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Alwyn Young: London School of Economics

Statistical Software Components from Boston College Department of Economics

Abstract: randcmdci computes randomization confidence intervals and p-values that are asymptotically robust to deviations from the sharp null in favour of average treatment effects for OLS regression models. Randomization inference of all forms is exact in finite samples when the sharp null is true (i.e. the treatment effect is the same for each and every observation). When the sharp null is not true and coefficients estimate the average of heterogeneous treatment effects, randomization inference in OLS regression based upon studentized test statistics, the randomization-t, has the same asymptotic validity as the clustered/robust covariance estimate provided the regressors have sufficiently high moments.

Language: Stata
Requires: Stata version 13.1
Keywords: regression; randomization; robust confidence intervals (search for similar items in EconPapers)
Date: 2021-12-30, Revised 2023-08-11
Note: This module should be installed from within Stata by typing "ssc install randcmdci". 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/r/randcmdci.sthlp help file (text/plain)
http://fmwww.bc.edu/repec/bocode/r/randcmdci.ado program code (text/plain)

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