同时发生的统治和理想点过程:一个一般的IRTree框架,用于多维项目响应
Viola Merhof1, Thorsten Meiser2
1Department of Psychology, University of Mannheim, L 13 15, D-68161, Mannheim, Germany. merhof@uni-mannheim.de.
Behavior research methods
|April 16, 2024
概括
一个新的DI-MIRT模型通过结合主导和理想点过程来增强IRTree模型. 这可以更准确地分析评级尺度项目中复杂的响应行为,提高测量精度.
科学领域:
- 心理测量 心理测量 心理测量
- 认知心理学 认知心理学
- 教育测量教育的测量
背景情况:
- 评级尺度项目响应受测量的特征和个人特征的影响.
- 项目响应理论 (IRT) 树 (IRTree) 模型将响应分析为连续的子决策.
- 现有的IRTree模型主要关注主导过程,限制了对其他响应理由的分析.
研究的目的:
- 为IRTree模型引入一个新的多维IRT模型 (DI-MIRT).
- 在IRTree子决策中整合同时发生的统治和理想点过程.
- 扩大IRTree模型的灵活性和应用范围,用于分析认知项目的响应.
主要方法:
- 为IRTree模型开发了DI-MIRT参数化.
- 将多重主导和理想点过程以及它们的组合纳入子决策.
- 进行模拟研究以评估参数恢复和模型准确性.
主要成果:
- DI-MIRT参数化准确地反映了同时发生的统治和理想点过程.
- 使用DI-MIRT参数化的IRTree模型显示出出色的参数恢复.
- 与纯粹顺序过程的传统IRTree模型相比,观察到一个显著的优势.
结论:
- 该DI-MIRT模型提供了一个灵活的框架,用于参数化IRTree子决策.
- 这种新模型扩展了适用于认知项目响应的理论假设.
- DI-MIRT模型增强了对响应风格的分析,并改善了在现实世界应用中的测量.
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