Department of Psychology, Chemnitz University of Technology, 09107, Chemnitz, Germany.
Behav Res Methods. 2012 Mar;44(1):144-57. doi: 10.3758/s13428-011-0130-8.
The article describes a general two-step procedure for the numerical translation of vague linguistic terms (LTs). The suggested procedure consists of empirical and model components, including (1) participants' estimates of numerical values corresponding to verbal terms and (2) modeling of the empirical data using fuzzy membership functions (MFs), respectively. The procedure is outlined in two studies for data from N = 89 and N = 109 participants, who were asked to estimate numbers corresponding to 11 verbal frequency expressions (e.g., sometimes). Positions and shapes of the resulting MFs varied considerably in symmetry, vagueness, and overlap and are indicative of the different meanings of the vague frequency expressions. Words were not distributed equidistantly across the numerical scale. This has important implications for the many questionnaires that use verbal rating scales, which consist of frequency expressions and operate on the premise of equidistance. These results are discussed for an exemplar questionnaire (COPSOQ). Furthermore, the variation of the number of prompted LTs (5 vs. 11) showed no influence on the words' interpretations.
本文描述了一种将模糊语言术语(LT)数值化的通用两步程序。该方法包括经验和模型两个组成部分,分别包括(1)参与者对与口头术语对应的数值的估计,以及(2)使用模糊隶属函数(MF)对经验数据进行建模。该程序在两项研究中进行了概述,其中一项研究的数据来自 N=89 名参与者,另一项研究的数据来自 N=109 名参与者,参与者被要求估计 11 个口头频率表达(例如有时)对应的数字。产生的 MF 的位置和形状在对称性、模糊性和重叠方面差异很大,这表明模糊频率表达的不同含义。词在数字刻度上不是等距分布的。这对许多使用口头评分量表的问卷有重要影响,这些问卷由频率表达组成,并基于等距的前提运行。对示例问卷(COPSOQ)进行了讨论。此外,提示的 LT 数量(5 个与 11 个)的变化对单词的解释没有影响。