R-Package LNIRT用于响应精度和时间的联合建模
Jean-Paul Fox1, Konrad Klotzke1, Ahmet Salih Simsek2
1Faculty of Behavioral, Management, and Social Sciences, University of Twente, Enschede, Netherlands.
PeerJ. Computer science
|June 22, 2023
概括
本研究介绍了LNIRT R包,用于计算机测试中的响应精度和响应时间的联合建模. 它通过整合工作数据的速度来改进测试分析来增强潜变量测量.
科学领域:
- 心理测量 心理测量 心理测量
- 教育测量教育的测量
- 统计软件 统计软件
背景情况:
- 基于计算机的测试通常收集响应精度 (RA) 和响应时间 (RT).
- 项目响应理论 (IRT) 模型传统上使用RA用于隐性变量测量 (例如能力).
- RT数据为工作速度提供了洞察力,并可以增强测试分析.
研究的目的:
- 引入LNIRT R包,用于安装集成RA和RT数据的关节模型.
- 展示联合模型如何改善潜变量估计,并提供对响应速度的见解.
- 提供一个用户友好的工具,用于在教育和心理测试中进行高级心理测量分析.
主要方法:
- 在R.中开发和应用LNIRT R包.
- 使用联合建模方法,同时分析响应精度和响应时间.
- 采用吉布斯采样进行模型拟合,可选的MCMC分析工具 (coda,mcmcse).
主要成果:
- 该LNIRT包提供了一个简化的接口,用于安装复杂的联合IRT模型.
- 证明了整合RT数据的实用性,以便更全面地了解考生特征.
- 将软件包成功应用于两个真实世界的数据集,验证其功能.
结论:
- 该LNIRT套件有助于将响应时间数据整合到心理测量分析中.
- 通过结合工作速度信息,联合建模提供了更丰富的潜在变量评估.
- 这种方法增强了基于计算机的测试对测量和运营洞察力的实用性.
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