QTest: Quantitative Testing of Theories of Binary Choice.
QTest: Quantitative Testing of Theories of Binary Choice.
复制标题
QTest：二元选择理论的定量测试。
DOI：
10.1037/dec0000007
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Messner,William
中科院分区：
文献类型：
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作者：
Regenwetter,Michel;Davis-Stober,ClintinP;Lim,ShiauHong;Guo,Ying;Popova,Anna;Zwilling,Chris;Cha,Yun-Shil;Messner,William
本文的目标是使建模和定量测试访问的行为决策研究人员感兴趣的实质性问题。我们提供了一个新的，严格的，但非常普遍的，定量诊断框架测试理论的二元选择。这使得非技术性学者能够远远超越传统的、相当肤浅的分析方法，也使得精通定量分析的学者能够在投入精力进行复杂而专门的定量分析之前，对理论建议进行分类。我们的理论框架将静态代数决策理论与行为二元选择数据中观察到的变异性联系起来。本文还补充了一个定制设计的公共领域统计分析软件包QTest。我们说明了我们的方法与定量分析使用已发表的实验室数据，包括测试的新版本的“随机累积前景理论”。该方法的一个主要优点是有可能区分决策者谁有一个固定的偏好，并在观察到的选择决策者谁在他们的偏好动摇犯错误。（PsycInfo数据库记录（c）2020阿帕，保留所有权利）
The goal of this paper is to make modeling and quantitative testing accessible to behavioral decision researchers interested in substantive questions. We provide a novel, rigorous, yet very general, quantitative diagnostic framework for testing theories of binary choice. This permits the nontechnical scholar to proceed far beyond traditionally rather superficial methods of analysis, and it permits the quantitatively savvy scholar to triage theoretical proposals before investing effort into complex and specialized quantitative analyses. Our theoretical framework links static algebraic decision theory with observed variability in behavioral binary choice data. The article is supplemented with a custom-designed public-domain statistical analysis package, the QTest software. We illustrate our approach with a quantitative analysis using published laboratory data, including tests of novel versions of “Random Cumulative Prospect Theory.” A major asset of the approach is the potential to distinguish decision makers who have a fixed preference and commit errors in observed choices from decision makers who waver in their preferences.(PsycInfo Database Record (c) 2020 APA, all rights reserved)