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社会科学中的量级估计和类别评定量表:一场理论与心理测量学的争论。

Magnitude estimation and categorical rating scaling in social sciences: a theoretical and psychometric controversy.

作者信息

Beltyukova Svetlana A, Stone Gregory E, Fox Christine M

机构信息

The University of Toledo, Research and Measurement, Toledo, OH 43606, USA.

出版信息

J Appl Meas. 2008;9(2):151-9.

Abstract

This paper revisits a half-century long theoretical controversy associated with the use of magnitude estimation scaling (MES) and category rating scaling (CRS) procedures in measurement. The MES procedure in this study involved instructing participants to write a number that matched their impression of difficulty of a test item. Participants were not restricted in the range of numbers they could choose for their scale. They also had the choice of disclosing their individual scale. After the MES task was completed, participants were given a blank copy of the test to rate the perceived difficulty of each item using a researcher-imposed categorical rating scale from 1 (very easy) to 6 (very difficult). The MES and CRS data were both analyzed using Rasch Rating scale model. Additionally, the MES data were examined with Rasch Partial Credit model. Results indicate that knowing each person's scale is associated with smaller errors of measurement.

摘要

本文重新审视了一场长达半个世纪的理论争议,该争议与测量中量级估计量表法(MES)和类别评定量表法(CRS)程序的使用有关。本研究中的MES程序要求参与者写下一个数字,该数字要与他们对测试项目难度的印象相匹配。参与者在为量表选择数字的范围上不受限制。他们也可以选择公开自己的个人量表。在MES任务完成后,会给参与者一份测试的空白副本,让他们使用研究人员设定的从1(非常容易)到6(非常困难)的类别评定量表对每个项目的感知难度进行评级。MES和CRS数据均使用拉施克评定量表模型进行分析。此外,MES数据还使用拉施克部分计分模型进行检验。结果表明,了解每个人的量表与较小的测量误差相关。

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