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 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