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Application of multidimensional item response theory models to longitudinal data

机译：多维项目响应理论模型在纵向数据中的应用

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摘要

The application of multidimensional item response theory (IRT) models to longitudinal educational surveys where students are repeatedly measured is discussed and exemplified. A marginal maximum likelihood (MML) method to estimate the parameters of a multidimensional generalized partial credit model for repeated measures is presented. It is shown that model fit can be evaluated using Lagrange multiplier tests. Two tests are presented: the first aims at evaluation of the fit of the item response functions and the second at the constancy of the item location parameters over time points. The outcome of the latter test is compared with an analysis using scatter plots and linear regression. An analysis of data from a school effectiveness study in Flanders (Belgium) is presented as an example of the application of these methods. In the example, it is evaluated whether the concepts "academic self-concept," "well-being at school," and "attentiveness in the classroom" were constant during the secondary school period.
机译：讨论并举例说明了多维项目反应理论（IRT）模型在纵向教育调查中的应用，在该调查中反复测量了学生。提出了一种边际最大似然（MML）方法来估计多维度量部分信用模型的重复测量。结果表明，可以使用拉格朗日乘数检验来评估模型拟合。提出了两个测试：第一个测试旨在评估项目响应函数的拟合度，第二个测试针对时间点上的项目定位参数的稳定性。将后者测试的结果与使用散点图和线性回归的分析进行比较。作为对这些方法的应用的一个例子，提出了一项对来自法兰德斯（比利时）的学校有效性研究的数据的分析。在该示例中，评估了中学时期的“学术自我概念”，“学校幸福感”和“课堂注意力”的概念是否恒定。

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