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Crowdsourcing hypothesis tests: Making transparent how design choices shape research results.
Psychological Bulletin ( IF 17.3 ) Pub Date : 2020-01-16 , DOI: 10.1037/bul0000220
Justin F Landy 1 , Miaolei Liam Jia 2 , Isabel L Ding 3 , Domenico Viganola 4 , Warren Tierney 5 , Anna Dreber 6 , Magnus Johannesson 6 , Thomas Pfeiffer 7 , Charles R Ebersole 8 , Quentin F Gronau 9 , Alexander Ly 9 , Don van den Bergh 9 , Maarten Marsman 9 , Koen Derks 10 , Eric-Jan Wagenmakers 9 , Andrew Proctor 6 , Daniel M Bartels 11 , Christopher W Bauman 12 , William J Brady 13 , Felix Cheung 14 , Andrei Cimpian 13 , Simone Dohle 15 , M Brent Donnellan 16 , Adam Hahn 15 , Michael P Hall 17 , William Jiménez-Leal 18 , David J Johnson 19 , Richard E Lucas 16 , Benoît Monin 20 , Andres Montealegre 18 , Elizabeth Mullen 21 , Jun Pang 22 , Jennifer Ray 13 , Diego A Reinero 13 , Jesse Reynolds 23 , Walter Sowden 17 , Daniel Storage 24 , Runkun Su 25 , Christina M Tworek 26 , Jay J Van Bavel 13 , Daniel Walco 27 , Julian Wills 13 , Xiaobing Xu 28 , Kai Chi Yam 29 , Xiaoyu Yang 30 , William A Cunningham 31 , Martin Schweinsberg 32 , Molly Urwitz 6 , The Crowdsourcing Hypothesis Tests Collaboration , Eric L Uhlmann 33
Affiliation  

To what extent are research results influenced by subjective decisions that scientists make as they design studies? Fifteen research teams independently designed studies to answer five original research questions related to moral judgments, negotiations, and implicit cognition. Participants from 2 separate large samples (total N > 15,000) were then randomly assigned to complete 1 version of each study. Effect sizes varied dramatically across different sets of materials designed to test the same hypothesis: Materials from different teams rendered statistically significant effects in opposite directions for 4 of 5 hypotheses, with the narrowest range in estimates being d = -0.37 to + 0.26. Meta-analysis and a Bayesian perspective on the results revealed overall support for 2 hypotheses and a lack of support for 3 hypotheses. Overall, practically none of the variability in effect sizes was attributable to the skill of the research team in designing materials, whereas considerable variability was attributable to the hypothesis being tested. In a forecasting survey, predictions of other scientists were significantly correlated with study results, both across and within hypotheses. Crowdsourced testing of research hypotheses helps reveal the true consistency of empirical support for a scientific claim. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

中文翻译:

众包假设检验:使设计选择如何影响研究结果透明。

研究结果在多大程度上受到科学家在设计研究时所做出的主观决定的影响?15个研究团队独立设计了研究,以回答与道德判断,谈判和内隐认知有关的五个原始研究问题。然后将来自2个单独的大样本(总N> 15,000)的参与者随机分配以完成每个研究的1个版本。在设计用于检验相同假设的不同材料集上,效果大小差异很大:来自不同团队的材料对5个假设中的4个在相反方向上产生了统计上显着的效果,估计值的最窄范围为d = -0.37至+ 0.26。荟萃分析和贝叶斯对结果的看法表明,总体支持2个假设,而缺乏对3个假设的支持。总体,实际上,效应大小的可变性都不归因于研究团队在设计材料方面的技能,而相当大的可变性归因于所检验的假设。在一项预测调查中,其他科学家的预测在假设范围之内和之内都与研究结果显着相关。对研究假设的众包测试有助于揭示对科学主张的经验支持的真实一致性。(PsycInfo数据库记录(c)2020 APA,保留所有权利)。在假设之内和之中。对研究假设的众包测试有助于揭示对科学主张的经验支持的真实一致性。(PsycInfo数据库记录(c)2020 APA,保留所有权利)。在假设之内和之中。对研究假设的众包测试有助于揭示对科学主张的经验支持的真实一致性。(PsycInfo数据库记录(c)2020 APA,保留所有权利)。
更新日期:2020-01-16
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