一种基于树的方法来识别锚定小片段的回应风格

IF 0.6 Q3 SOCIAL SCIENCES, INTERDISCIPLINARY
B. Leventhal, C. Zigler
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引用次数: 1

摘要

调查分数的解释经常受到构念无关变异的来源的困扰,例如回答风格。在本研究中,我们建议使用IRTree模型通过使用自我报告项目和锚定小片段来解释反应风格。具体来说,我们研究了带有锚定小片段的IRTree方法与不包含锚定小片段或不考虑响应风格的传统方法相比如何。我们使用四种不同的模型分析二手数据:1)总分;2)分级响应模型;3)不考虑锚点的IRTree和4)考虑锚点的IRTree。我们发现,与那些不考虑反应风格的模型相比,考虑反应风格的模型在性状估计上存在显著差异。此外,我们发现IRTree模型在考虑锚定小片段和不考虑锚定小片段时的性状估计存在差异。模型比较表明,性状差异是由于对默认反应方式的调整。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Tree-Based Approach to Identifying Response Styles with Anchoring Vignettes
ABSTRACT Survey score interpretations are often plagued by sources of construct-irrelevant variation, such as response styles. In this study, we propose the use of an IRTree Model to account for response styles by making use of self-report items and anchoring vignettes. Specifically, we investigate how the IRTree approach with anchoring vignettes compares to traditional approaches that either do not include anchoring vignettes or do not account for response styles. We analyze secondary data using four different models: 1) total score; 2) graded response model; 3) IRTree without the consideration of anchoring vignettes, and 4) IRTree considering anchoring vignettes. We found significant differences in trait estimates from models that account for response styles compared to those that do not. Additionally, we found differences in trait estimates between the IRTree Models when considering anchoring vignettes and when not. Model comparisons suggest that trait differences are due to adjusting for acquiescence response style.
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来源期刊
Measurement-Interdisciplinary Research and Perspectives
Measurement-Interdisciplinary Research and Perspectives SOCIAL SCIENCES, INTERDISCIPLINARY-
CiteScore
1.80
自引率
0.00%
发文量
23
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