跨小群体自我报告测量中检测项目措辞效应的心理测量网络分析方法

IF 1.1 3区社会学 Q2 ANTHROPOLOGY

Field Methods Pub Date : 2024-05-11 DOI:10.1177/1525822x241247444

H. Cigdem Bulut, Okan Bulut, Ashley Clelland

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引用次数: 0

摘要

在本研究中，我们探索了心理测量网络分析（PNA），将其作为识别自我报告工具中项目措辞效应的另一种方法。我们考察了 2019 年国际数学与科学研究趋势（TIMSS）中两个与数学相关的量表--"学生喜欢学习数学"（SLLM）和 "学生对数学有信心"（SCM）的网络结构中消极措辞项目的功能。我们还探讨了消极措辞的项目如何在不同人口亚群的网络结构中发挥作用。数据来自八个国家，代表了不同的数学成绩水平和对学校的文化态度（n = 75972）。我们发现，在 SLLM 和 SCM 项目网络中，消极措辞的项目与积极措辞的项目截然不同，而且这种效应在所有年龄和国家级别的亚组中都是一致的。基于这些发现，我们建议将 PNA 作为有效检测措辞效应的数据驱动方法。

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A Psychometric Network Analysis Approach for Detecting Item Wording Effects in Self-report Measures across Subgroups

In this study, we explored psychometric network analysis (PNA) as an alternative method for identifying item wording effects in self-report instruments. We examined the functioning of negatively worded items in the network structures of two math-related scales from the 2019 Trends in International Mathematics and Science Study (TIMSS); Students Like Learning in Mathematics (SLLM); and Students Confident in Mathematics (SCM). We also explored how the negatively worded items functioned in network structures across demographic subgroups. Data were drawn from eight countries that represented diverse levels of math performance and cultural attitudes toward school ( n = 75,972). We found that negatively worded items were distinct from the positively worded items in the SLLM and SCM item networks, and that this effect was consistent across all age- and country-level subgroups. Based on these findings, we recommend PNA as a data-driven approach for detecting wording effects effectively.

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来源期刊

Field Methods Multiple-

CiteScore

2.70

自引率

5.90%

发文量

期刊介绍： Field Methods (formerly Cultural Anthropology Methods) is devoted to articles about the methods used by field wzorkers in the social and behavioral sciences and humanities for the collection, management, and analysis data about human thought and/or human behavior in the natural world. Articles should focus on innovations and issues in the methods used, rather than on the reporting of research or theoretical/epistemological questions about research. High-quality articles using qualitative and quantitative methods-- from scientific or interpretative traditions-- dealing with data collection and analysis in applied and scholarly research from writers in the social sciences, humanities, and related professions are all welcome in the pages of the journal.