• Media type: E-Book
  • Title: Non-Standard Errors
  • Contributor: Menkveld, Albert J. [Author]; Dreber, Anna [Author]; Holzmeister, Felix [Author]; Huber, Juergen [Author]; Johannesson, Magnus [Author]; Kirchler, Michael [Author]; Neusüss, Sebastian [Author]; Razen, Michael [Author]; Weitzel, Utz [Author]
  • Published: [S.l.]: SSRN, [2021]
  • Published in: Tinbergen Institute Discussion Paper 2021-102/IV
  • Extent: 1 Online-Ressource (63 p)
  • Language: English
  • DOI: 10.2139/ssrn.3981597
  • Identifier:
  • Origination:
  • Footnote: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments November 13, 2021 erstellt
  • Description: In statistics, samples are drawn from a population in a data- generating process (DGP). Standard errors measure the uncer- tainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants
  • Access State: Open Access