Do People Prefer to Give Interval-Valued or Point Estimates and Why?

Zack Ellerby, Christian Wagner
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引用次数: 6

Abstract

Capturing interval-valued, as opposed to more conventional point-valued data, offers a potentially efficient method of obtaining richer information in individual responses. In turn, interval-valued data provide a strong foundation for subsequent fuzzy set based modelling-e.g., using the Interval Agreement Approach. In 2019, open-source software (DECSYS) was released to enable digital administration of interval-valued surveys using an ellipse response mode. This study follows on from an appraisal of this software and demonstration of practical value of the approach, reported last year, in one of many potential real-world applications (consumer preference research). A key ambition of ellipse-based interval elicitation is to maximise response efficiency-i.e., minimising workload and complexity in obtaining this richer information. User experience is therefore a vital consideration regarding potential for broader adoption. The present paper documents a direct empirical comparison between interval-valued response elicitation (using ellipses) and a conventional point-valued counterpart (using a Visual Analogue Scale), in terms of user experience during completion of a simple quantitative estimation task. We examine differences in perceived ease-of-use, unnecessary complexity and effective communication of desired responses, as well as overall liking-with positive outcomes for the interval-valued response mode in each case. We also report results of multiple regression analyses examining how the first three variables contribute to participants' overall liking of each response mode, as well as exploring differences driven by potentially important demographic factors (i.e., gender, age & native English speaking).
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人们更喜欢给出区间值还是点估计?为什么?
与更传统的点值数据相反,捕获区间值数据提供了一种潜在的有效方法,可以在单个响应中获得更丰富的信息。反过来,区间值数据为后续基于模糊集的建模提供了坚实的基础。,使用间隔协议方法。2019年,开源软件(DECSYS)发布,可以使用椭圆响应模式对区间值调查进行数字化管理。这项研究是继去年对该软件的评估和该方法的实用价值的演示之后进行的,该方法在许多潜在的现实世界应用之一(消费者偏好研究)。基于椭圆的区间提取的一个关键目标是最大限度地提高响应效率。,最大限度地减少了获得这些更丰富信息的工作量和复杂性。因此,用户体验是考虑更广泛应用的重要因素。本文记录了在完成简单定量估计任务期间的用户体验方面,区间值响应引出(使用省略号)和传统点值对应(使用视觉模拟量表)之间的直接经验比较。我们研究了在感知易用性、不必要的复杂性和期望响应的有效沟通方面的差异,以及总体上的喜欢程度——在每种情况下,区间值响应模式都有积极的结果。我们还报告了多元回归分析的结果,研究了前三个变量如何影响参与者对每种反应模式的总体喜好,以及探索由潜在重要的人口因素(即性别、年龄和母语英语)驱动的差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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