Nonstandard Errors Article Swipe
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Albert J. Menkveld
,
Anna Dreber
,
Felix Holzmeister
,
Jürgen Huber
,
Magnus Johannesson
,
Michael Kirchler
,
Sebastian Neusüss
,
Michael Razen
,
Utz Weitzel
,
DAVID ABAD‐DÍAZ
,
Menachem Abudy
,
Tobias Adrian
,
Yacine Aït‐Sahalia
,
Olivier Akmansoy
,
Jamie Alcock
,
Vitali Alexeev
,
Arash Aloosh
,
Livia Amato
,
Diego Amaya
,
James J. Angel
,
ALEJANDRO T. AVETIKIAN
,
Amadeus Bach
,
Edwin Baidoo
,
Gaetan Bakalli
,
Bao Li
,
Andrea Barbon
,
Oksana Bashchenko
,
Parampreet Christopher Bindra
,
Geir Høidal Bjønnes
,
Jeffrey R. Black
,
Bernard S. Black
,
Dimitar Bogoev
,
SANTIAGO BOHORQUEZ CORREA
,
Oleg Bondarenko
,
Charles S. Bos
,
Ciril Bosch-Rosa
,
Elie Bouri
,
Christian T. Brownlees
,
Anna Calamia
,
Viet Nga Cao
,
Gunther Capelle‐Blancard
,
LAURA M. CAPERA ROMERO
,
Massimiliano Caporin
,
Allen Carrion
,
Tolga Caskurlu
,
Bidisha Chakrabarty
,
Jian Chen
,
Mikhail Chernov
,
William Cheung
,
Ludwig B. Chincarini
,
Tarun Chordia
,
SHEUNG‐CHI CHOW
,
Benjamin Clapham
,
Jean-Édouard Colliard
,
Carole Comerton‐Forde
,
Edward T. Curran
,
Thông Dao
,
Wale Dare
,
Ryan J. Davies
,
Riccardo De Blasis
,
GIANLUCA F. DE NARD
,
Fany Declerck
,
Oleg Deev
,
Hans Degryse
,
Solomon Y. Deku
,
Christophe Desagre
,
Mathijs A. van Dijk
,
Chukwuma Dim
,
Thomas Dimpfl
,
Yun Jiang Dong
,
P. Drummond
,
Tom L. Dudda
,
Teodor Duevski
,
Ariadna Dumitrescu
,
Teodor Dyakov
,
Anne Haubo Dyhrberg
,
Michał Dzieliński
,
Asli Eksi
,
Izidin El Kalak
,
Saskia ter Ellen
,
Nicolas Eugster
,
Martin D.D. Evans
,
Michael Farrell
,
ESTER FELEZ‐VINAS
,
Gerardo Ferrara
,
El Mehdi Ferrouhi
,
Andrea Flori
,
Jonathan Fluharty-Jaidee
,
Sean Foley
,
Kingsley Y. L. Fong
,
Thierry Foucault
,
Tatiana Franus
,
Francesco A. Franzoni
,
Bart Frijns
,
Michael Frömmel
,
SERVANNA M. FU
,
Sascha Füllbrunn
,
Baoqing Gan
,
Ge Gao
,
Thomas Gehrig
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1111/jofi.13337
· OA: W4394881644
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1111/jofi.13337
· OA: W4394881644
In statistics, samples are drawn from a population in a data‐generating process (DGP). Standard errors measure the uncertainty in 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—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer‐review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.
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