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A general-purpose method for two-group randomization tests

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Author Info

  • Johannes Kaiser

    ()
    (Laboratory for Experimental Economics, University of Bonn)

  • Michael G. Lacy

    ()
    (Colorado State University)

Abstract

We outline a novel approach to calculate exact p-levels for two-sample randomization tests. The approach closely resembles permute in its applications, with the main difference being that the results are approximated only if the execution time needed to calculate exact p-levels would exceed a specified maximum. We demonstrate its use by deriving p-levels for the significance of Somers’ D, the coefficient of variation, the difference in means and in medians, and the difference in two multinomials. Copyright 2009 by StataCorp LP.

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Bibliographic Info

Article provided by StataCorp LP in its journal Stata Journal.

Volume (Year): 9 (2009)
Issue (Month): 1 (March)
Pages: 70-85

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Handle: RePEc:tsj:stataj:v:9:y:2009:i:1:p:70-85

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Related research

Keywords: tsrtest; mwtest; fptest; somersdtest; cvtest; vartest; randomization tests; Monte Carlo; two-sample problem;

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Cited by:
  1. Cheung, Stephen L. & Hedegaard, Morten & Palan, Stefan, 2014. "To see is to believe: Common expectations in experimental asset markets," European Economic Review, Elsevier, vol. 66(C), pages 84-96.
  2. Daniele Nosenzo & Theo Offerman & Martin Sefton & Ailko van der Veen, 2012. "Discretionary Sanctions and Reward in the Repeated Inspection Game," Discussion Papers 2012-10, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.
  3. Daniele Nosenzo & Theo Offerman & Martin Sefton & Ailko van der Veen, 2014. "Discretionary Sanctions and Rewards in the Repeated Inspection Game," Discussion Papers 2014-04, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.

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