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A novel Likert scale based on fuzzy sets theory

机译：基于模糊集理论的新型李克特量表

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The Likert method is commonly used as a standard psychometric scale to measure responses. This measurement scale has a procedure that facilitates survey construction and administration, and data coding and analysis. However, there are some drawbacks in the Likert scaling. This paper addresses the information distortion and information lost arising from the closed-form scaling and the ordinal nature of this measurement method. To overcome these problems, a novel fuzzy Likert scale developed based on the fuzzy sets theory has been proposed. The major contribution of the fuzzy Likert approach is that it permits partial agreement of a scale point. By incorporating this capability into the measurement process, the new scale can capture the lost information and regulate the distorted information. A quantitative analysis based on the concept Consensus has proven that the new scale can provide a more accurate measurement. The implementation feasibility and the improved measurement performance of the fuzzy Likert scale have been demonstrated via a simulation study on a low birth weight analysis.
机译：Likert方法通常用作衡量反应的标准心理量表。该度量标准具有促进调查的构建和管理以及数据编码和分析的过程。但是，李克特缩放存在一些缺点。本文讨论了由于闭合形式的缩放和这种测量方法的序数性质而导致的信息失真和信息丢失。为了克服这些问题，提出了一种基于模糊集理论的新型模糊李克特量表。模糊李克特方法的主要贡献是它允许比例尺部分一致。通过将此功能整合到测量过程中，新秤可以捕获丢失的信息并调整失真的信息。基于共识概念的定量分析证明，新秤可以提供更准确的测量结果。通过对低出生体重分析的模拟研究，证明了模糊李克特量表的实施可行性和改进的测量性能。

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