Literature DB >> 34002054

The natural selection of good science.

Alexander J Stewart1, Joshua B Plotkin2.   

Abstract

Scientists in some fields are concerned that many published results are false. Recent models predict selection for false positives as the inevitable result of pressure to publish, even when scientists are penalized for publications that fail to replicate. We model the cultural evolution of research practices when laboratories are allowed to expend effort on theory, enabling them, at a cost, to identify hypotheses that are more likely to be true, before empirical testing. Theory can restore high effort in research practice and suppress false positives to a technical minimum, even without replication. The mere ability to choose between two sets of hypotheses, one with greater prior chance of being correct, promotes better science than can be achieved with effortless access to the set of stronger hypotheses. Combining theory and replication can have synergistic effects. On the basis of our analysis, we propose four simple recommendations to promote good science.
© 2021. The Author(s), under exclusive licence to Springer Nature Limited.

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Year:  2021        PMID: 34002054     DOI: 10.1038/s41562-021-01111-x

Source DB:  PubMed          Journal:  Nat Hum Behav        ISSN: 2397-3374


  32 in total

1.  Measuring the prevalence of questionable research practices with incentives for truth telling.

Authors:  Leslie K John; George Loewenstein; Drazen Prelec
Journal:  Psychol Sci       Date:  2012-04-16

2.  False-positive psychology: undisclosed flexibility in data collection and analysis allows presenting anything as significant.

Authors:  Joseph P Simmons; Leif D Nelson; Uri Simonsohn
Journal:  Psychol Sci       Date:  2011-10-17

3.  HARKing: hypothesizing after the results are known.

Authors:  N L Kerr
Journal:  Pers Soc Psychol Rev       Date:  1998

4.  P-curve: a key to the file-drawer.

Authors:  Uri Simonsohn; Leif D Nelson; Joseph P Simmons
Journal:  J Exp Psychol Gen       Date:  2013-07-15

Review 5.  Reproducibility in science: improving the standard for basic and preclinical research.

Authors:  C Glenn Begley; John P A Ioannidis
Journal:  Circ Res       Date:  2015-01-02       Impact factor: 17.367

6.  Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015.

Authors:  Colin F Camerer; Anna Dreber; Felix Holzmeister; Teck-Hua Ho; Jürgen Huber; Magnus Johannesson; Michael Kirchler; Gideon Nave; Brian A Nosek; Thomas Pfeiffer; Adam Altmejd; Nick Buttrick; Taizan Chan; Yiling Chen; Eskil Forsell; Anup Gampa; Emma Heikensten; Lily Hummer; Taisuke Imai; Siri Isaksson; Dylan Manfredi; Julia Rose; Eric-Jan Wagenmakers; Hang Wu
Journal:  Nat Hum Behav       Date:  2018-08-27

7.  SCIENTIFIC STANDARDS. Promoting an open research culture.

Authors:  B A Nosek; G Alter; G C Banks; D Borsboom; S D Bowman; S J Breckler; S Buck; C D Chambers; G Chin; G Christensen; M Contestabile; A Dafoe; E Eich; J Freese; R Glennerster; D Goroff; D P Green; B Hesse; M Humphreys; J Ishiyama; D Karlan; A Kraut; A Lupia; P Mabry; T A Madon; N Malhotra; E Mayo-Wilson; M McNutt; E Miguel; E Levy Paluck; U Simonsohn; C Soderberg; B A Spellman; J Turitto; G VandenBos; S Vazire; E J Wagenmakers; R Wilson; T Yarkoni
Journal:  Science       Date:  2015-06-26       Impact factor: 47.728

8.  Publication bias and the canonization of false facts.

Authors:  Silas Boye Nissen; Tali Magidson; Kevin Gross; Carl T Bergstrom
Journal:  Elife       Date:  2016-12-20       Impact factor: 8.140

9.  A manifesto for reproducible science.

Authors:  Marcus R Munafò; Brian A Nosek; Dorothy V M Bishop; Katherine S Button; Christopher D Chambers; Nathalie Percie du Sert; Uri Simonsohn; Eric-Jan Wagenmakers; Jennifer J Ware; John P A Ioannidis
Journal:  Nat Hum Behav       Date:  2017-01-10

10.  Why most published research findings are false.

Authors:  John P A Ioannidis
Journal:  PLoS Med       Date:  2005-08-30       Impact factor: 11.613

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