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
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Englisch
- Bibliographic citation
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Series: Tinbergen Institute Discussion Paper ; No. TI 2021-102/IV
- Classification
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Wirtschaft
Hypothesis Testing: General
Methodological Issues: General
- Event
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Geistige Schöpfung
- (who)
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Menkveld, Albert J.
Dreber, Anna
Holzmeister, Felix
Huber, Jürgen
Johannesson, Magnus
Kirchler, Michael
Neusüss, Sebastian
Razen, Michael
Weitzel, Utz
- Event
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Veröffentlichung
- (who)
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Tinbergen Institute
- (where)
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Amsterdam and Rotterdam
- (when)
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2021
- Handle
- Last update
- 10.03.2025, 11:44 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
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