使用瑟斯顿IRT模型构建强迫选择问卷的贡献。

IF 5.3 3区 心理学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Multivariate Behavioral Research Pub Date : 2024-03-01 Epub Date: 2023-09-30 DOI:10.1080/00273171.2023.2248979
Luning Sun, Zijie Qin, Shan Wang, Xuetao Tian, Fang Luo
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引用次数: 0

摘要

强迫选择问卷包括按块列出项目,并要求受访者提供每个块中项目的全部或部分排名。为了防止非自愿或自愿的反应扭曲,通常由具有相似可取程度的项目组成块。组装强迫选择块并不是一个微不足道的过程,因为除了合意性之外,还需要仔细考虑项目之间关系的方向和大小以及被测量的特征(即因素负载)。基于使用项目对的模拟和实证研究,我们就如何构建符合愿望的项目对提出了建议。当所有配对都包含指向同一方向的项目时,通过最大化块内加载差异来提高分数可靠性。即使是少量配对由不相等键控的项目组成,也可以获得更高的可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Contributions to Constructing Forced-Choice Questionnaires Using the Thurstonian IRT Model.

Forced-choice questionnaires involve presenting items in blocks and asking respondents to provide a full or partial ranking of the items within each block. To prevent involuntary or voluntary response distortions, blocks are usually formed of items that possess similar levels of desirability. Assembling forced-choice blocks is not a trivial process, because in addition to desirability, both the direction and magnitude of relationships between items and the traits being measured (i.e., factor loadings) need to be carefully considered. Based on simulations and empirical studies using item pairs, we provide recommendations on how to construct item pairs matched by desirability. When all pairs contain items keyed in the same direction, score reliability is improved by maximizing within-block loading differences. Higher reliability is obtained when even a small number of pairs consist of unequally keyed items.

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来源期刊
Multivariate Behavioral Research
Multivariate Behavioral Research 数学-数学跨学科应用
CiteScore
7.60
自引率
2.60%
发文量
49
审稿时长
>12 weeks
期刊介绍: Multivariate Behavioral Research (MBR) publishes a variety of substantive, methodological, and theoretical articles in all areas of the social and behavioral sciences. Most MBR articles fall into one of two categories. Substantive articles report on applications of sophisticated multivariate research methods to study topics of substantive interest in personality, health, intelligence, industrial/organizational, and other behavioral science areas. Methodological articles present and/or evaluate new developments in multivariate methods, or address methodological issues in current research. We also encourage submission of integrative articles related to pedagogy involving multivariate research methods, and to historical treatments of interest and relevance to multivariate research methods.
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