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Testing for heterogeneous treatment effects in experimental data: false discovery risks and correction procedures

Listed author(s):
  • Günther Fink
  • Margaret McConnell
  • Sebastian Vollmer
Registered author(s):

    We review the statistical models applied to test for heterogeneous treatment effects in the recent empirical literature, with a particular focus on data from randomised field experiments. We show that testing for heterogeneous treatment effects is highly common, and likely to result in a large number of false discoveries when conventional decision rules are applied. We demonstrate that applying correction procedures developed in the statistics literature can fully address this issue, and discuss the implications of multiple testing adjustments for power calculations and experimental design.

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    File URL: http://hdl.handle.net/10.1080/19439342.2013.875054
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    Article provided by Taylor & Francis Journals in its journal Journal of Development Effectiveness.

    Volume (Year): 6 (2014)
    Issue (Month): 1 (January)
    Pages: 44-57

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    Handle: RePEc:taf:jdevef:v:6:y:2014:i:1:p:44-57
    DOI: 10.1080/19439342.2013.875054
    Contact details of provider: Web page: http://www.tandfonline.com/RJDE20

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