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

Author

Listed:
  • Alwyn Young

    (London School of Economics)

Programming Language

Stata

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.

Suggested Citation

  • Alwyn Young, 2021. "RANDCMDCI: Stata module to produce robust randomization-t p-values and confidence intervals for regression coefficients," Statistical Software Components S459032, Boston College Department of Economics, revised 11 Aug 2023.
    • Handle: RePEc:boc:bocode:s459032
    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.
    as

    Download full text from publisher

    File URL: http://fmwww.bc.edu/repec/bocode/r/randcmdci.sthlp
    File Function: help file
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/r/randcmdci.ado
    File Function: program code
    Download Restriction: no
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