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自然频率对贝叶斯推理影响的荟萃分析。

Meta-analysis of the effect of natural frequencies on Bayesian reasoning.

机构信息

Harding Center for Risk Literacy, Max Planck Institute for Human Development.

Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development.

出版信息

Psychol Bull. 2017 Dec;143(12):1273-1312. doi: 10.1037/bul0000126. Epub 2017 Oct 19.

Abstract

The natural frequency facilitation effect describes the finding that people are better able to solve descriptive Bayesian inference tasks when represented as joint frequencies obtained through natural sampling, known as natural frequencies, than as conditional probabilities. The present meta-analysis reviews 20 years of research seeking to address when, why, and for whom natural frequency formats are most effective. We review contributions from research associated with the 2 dominant theoretical perspectives, the ecological rationality framework and nested-sets theory, and test potential moderators of the effect. A systematic review of relevant literature yielded 35 articles representing 226 performance estimates. These estimates were statistically integrated using a bivariate mixed-effects model that yields summary estimates of average performances across the 2 formats and estimates of the effects of different study characteristics on performance. These study characteristics range from moderators representing individual characteristics (e.g., numeracy, expertise), to methodological differences (e.g., use of incentives, scoring criteria) and features of problem representation (e.g., short menu format, visual aid). Short menu formats (less computationally complex representations showing joint-events) and visual aids demonstrated some of the strongest moderation effects, improving performance for both conditional probability and natural frequency formats. A number of methodological factors (e.g., exposure to both problem formats) were also found to affect performance rates, emphasizing the importance of a systematic approach. We suggest how research on Bayesian reasoning can be strengthened by broadening the definition of successful Bayesian reasoning to incorporate choice and process and by applying different research methodologies. (PsycINFO Database Record

摘要

自然频率促进效应描述了这样一种发现,即当人们以通过自然抽样获得的联合频率(即自然频率)而不是条件概率来表示描述性贝叶斯推理任务时,他们能够更好地解决这些任务。本元分析回顾了 20 年来寻求解决何时、为何以及对于谁来说自然频率格式最有效的研究。我们回顾了与 2 个主要理论观点(生态理性框架和嵌套集理论)相关的研究贡献,并检验了该效应的潜在调节因素。对相关文献进行系统回顾,得到了 35 篇文章,代表了 226 项绩效估计。使用二元混合效应模型对这些估计值进行了统计综合,该模型提供了两种格式下的平均绩效综合估计值,以及不同研究特征对绩效的影响估计值。这些研究特征包括代表个体特征(例如,计算能力、专业知识)的调节因素,到方法学差异(例如,使用激励措施、评分标准)和问题表示形式的特征(例如,短菜单格式、视觉辅助)。短菜单格式(显示联合事件的计算复杂度较低的表示)和视觉辅助显示出了一些最强的调节效应,提高了条件概率和自然频率格式的表现。还发现了一些方法学因素(例如,同时接触两种问题格式)也会影响绩效率,强调了系统方法的重要性。我们建议如何通过将成功的贝叶斯推理的定义扩展到包含选择和过程,并应用不同的研究方法,来加强贝叶斯推理研究。

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