古利克森池:一个快速工具,用于在项目因素分析中初步检测有问题的项目
Pere J Ferrando1, Urbano Lorenzo-Seva1, M Teresa Bargalló-Escrivà1
1Research Center for Behavioral Assessment, Universitat Rovira i Virgili, Tarragona, Spain.
PloS one
|August 25, 2023
概括
这项研究引入了一种新的程序,用于在规模开发过程中识别有问题的项目. 它通过在分析之前标记不合适的项目来增强探索性因子分析,改善维度评估.
科学领域:
- 心理测量 心理测量 心理测量
- 统计分析 统计分析
背景情况:
- 探索性因子分析 (EFA) 对于规模开发至关重要,但有问题的项目可能会阻碍准确的维度评估.
- 不有效的项目使规模构建的早期阶段复杂化,影响结果的可靠性.
研究的目的:
- 在EFA中指定因数式解决方案之前,提出和实施一个标记潜在问题项的程序.
- 通过早期识别和排除不合适的项目来增强规模开发中的项目分析过程.
主要方法:
- 开发了一种基于项目极端性和一致性的程序,以定义项目适当性和效率的区域.
- 使用广泛的模拟来确定在现实的应用条件下适宜区域的极限.
- 定义了一个项目响应理论 (IRT) 索引,用于先前的项目效率,并提出了对项目子集选择的综合方法.
主要成果:
- 拟议的程序有效地标记了可能存在问题的项目,提高了EFA维度和结构评估的准确性.
- 该方法提供了一种强大的方法来选择更有效和无问题的项目子集用于规模开发.
- 该程序对于正常范围的测量和人格调查问卷特别有用.
结论:
- 实施的程序为从事规模开发的研究人员提供了有价值的工具,特别是在使用EFA时.
- 这种方法有助于缓解由不合适的项目引起的问题,导致更可靠和有效的测量仪器.
- 免费软件实现使得这个先进的项目分析技术可供更广泛的研究社区使用.
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