强制选择问卷中的维度评估:迈向探索性框架的第一步
Diego F Graña1, Rodrigo S Kreitchmann2, Miguel A Sorrel1
1Universidad Autónoma de Madrid, Madrid, Spain.
Educational and psychological measurement
|September 12, 2025
概括
本研究评估了评估强制选择 (FC) 调查问卷结构的方法. 平行分析 (PA) 和最大凯泽标准在确定FC数据的维数时表现出卓越的准确性.
科学领域:
- 心理测量 心理测量 心理测量
- 量化心理学 量化心理学
- 调查方法 调查方法
背景情况:
- 强制选择 (FC) 问卷被用来尽量减少自我报告中的社会可取性偏见.
- 对于FC数据的确认模型假设已知的结构,这些结构可能不符合经验数据.
- 探索性模型通常是必要的,需要准确的维度评估.
研究的目的:
- 系统地评估五个维度评估方法对FC问卷数据的性能.
- 确定最准确和最不偏的方法来确定FC数据中的维数.
- 为FC问卷设计和分析提供实际建议.
主要方法:
- 进行了一项蒙特卡洛模拟研究.
- 检查了五种维度评估方法:凯泽标准,实证凯泽标准,并行分析 (PA),船体方法和探索图分析.
- 模拟的FC数据在维度,每个维度的项目,响应格式,块组成,因子负载,因子间相关性和样本大小方面各不相同.
主要成果:
- 最大凯泽标准和并行分析 (PA) 方法显示了最高的准确性和最低的偏差.
- 随着纳入异极或单维块,方法性能得到了改善.
- 问卷长度增加也提高了这些方法的性能.
结论:
- 建议在强制选择问卷中使用并行分析 (PA) 和最大凯泽标准进行维度评估.
- 周到的问卷设计,包括块组成,对于准确的维度评估至关重要.
- 这些发现为使用FC问卷调查的研究人员提供了实际指导.
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