Arbeitspapier

Non-standard errors

In statistics, samples are drawn from a population in a datagenerating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidencegenerating 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.

Language
Englisch

Bibliographic citation
Series: Tinbergen Institute Discussion Paper ; No. TI 2021-102/IV

Classification
Wirtschaft
Hypothesis Testing: General
Methodological Issues: General

Event
Geistige Schöpfung
(who)
Menkveld, Albert J.
Dreber, Anna
Holzmeister, Felix
Huber, Jürgen
Johannesson, Magnus
Kirchler, Michael
Neusüss, Sebastian
Razen, Michael
Weitzel, Utz
Event
Veröffentlichung
(who)
Tinbergen Institute
(where)
Amsterdam and Rotterdam
(when)
2021

Handle
Last update
10.03.2025, 11:44 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Menkveld, Albert J.
  • Dreber, Anna
  • Holzmeister, Felix
  • Huber, Jürgen
  • Johannesson, Magnus
  • Kirchler, Michael
  • Neusüss, Sebastian
  • Razen, Michael
  • Weitzel, Utz
  • Tinbergen Institute

Time of origin

  • 2021

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