 Non-Standard ErrorsChristian Wolff,
Albert Menkveld,
Anna Dreber,
Felix Holzmeister,
Juergen Huber,
Magnus Johannesson,
Michael Kirchler,
Neusüess, Sebastian,
Michael Razen and
Utz Weitzel
No 16751, CEPR Discussion Papers from C.E.P.R. Discussion Papers Abstract: In statistics, samples are drawn from a population in a data generating process (DGP). Standard errors measure the uncertainty 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. Date: 2021-11 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:cpr:ceprdp:16751 Ordering information: This working paper can be ordered from Access Statistics for this paper More papers in CEPR Discussion Papers from C.E.P.R. Discussion Papers Centre for Economic Policy Research, 33 Great Sutton Street, London EC1V 0DX. |
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