Different methods elicit different belief distributions.

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-09-26 DOI:10.1037/xge0001655
Beidi Hu,Joseph P Simmons
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Abstract

When eliciting people's forecasts or beliefs, you can ask for a point estimate-for example, what is the most likely state of the world?-or you can ask for an entire distribution of beliefs-for example, how likely is every possible state of the world? Eliciting belief distributions potentially yields more information, and researchers have increasingly tried to do so. In this article, we show that different elicitation methods elicit different belief distributions. We compare two popular methods used to elicit belief distributions: Distribution Builder and Sliders. In 10 preregistered studies (N = 14,553), we find that Distribution Builder elicits more accurate belief distributions than Sliders, except when true distributions are right-skewed, for which the results are mixed. This result holds when we assess accuracy (a) relative to a normative benchmark and (b) relative to participants' own beliefs. Our evidence suggests that participants approach these two methods differently: Sliders users are more likely to start with the lowest bins in the interface, which in turn leads them to put excessive mass in those bins. Our research sheds light on the process by which people construct belief distributions while offering a practical recommendation for future research: All else equal, Distribution Builder yields more accurate belief distributions. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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不同的方法会产生不同的信念分布。
在征询人们的预测或信念时,您可以询问一个估计点,例如,世界上最有可能出现的状况是什么;您也可以询问整个信念分布,例如,世界上每一种可能出现的状况的可能性有多大?激发信念分布可能会获得更多信息,研究人员也越来越多地尝试这样做。在本文中,我们将展示不同的诱导方法会诱发出不同的信念分布。我们比较了两种常用的信念分布诱导方法:分布生成器和滑块。在 10 项预先登记的研究(N = 14553)中,我们发现分布生成器比滑动器能引出更准确的信念分布,除非真实分布是右偏的,在这种情况下结果不一。当我们评估(a)相对于规范基准和(b)相对于参与者自身信念的准确性时,这一结果是成立的。我们的证据表明,参与者采用这两种方法的方式不同:滑块用户更有可能从界面中最低的箱开始,这反过来又会导致他们在这些箱中放入过多的质量。我们的研究揭示了人们构建信念分布的过程,同时也为未来的研究提供了切实可行的建议:在其他条件相同的情况下,"分布生成器 "能生成更准确的信念分布。(PsycInfo 数据库记录 (c) 2024 APA,保留所有权利)。
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来源期刊
CiteScore
7.20
自引率
4.30%
发文量
567
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