Target Rotations and Assessing the Impact of Model Violations on the Parameters of Unidimensional Item Response Theory Models
Target Rotations and Assessing the Impact of Model Violations on the Parameters of Unidimensional Item Response Theory Models
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DOI：
10.1177/0013164410378690
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发表时间：
2011-08-01
影响因子：
2.7
通讯作者：
Maydeu-Olivares, Alberto
中科院分区：
文献类型：
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作者：
Reise, Steven;Moore, Tyler;Maydeu-Olivares, Alberto
Reise、Cook 和 Moore 提出了一种“比较建模”方法，用于评估将一维项目响应理论 (IRT) 模型应用于多维数据时项目参数估计值的失真。他们的方法的核心是将来自一维 IRT 模型（受限模型）的项目斜率参数估计值与来自探索性双因子 IRT 模型（非限制比较模型）中的一般因子的项目斜率参数估计值进行比较。反过来，这些作者建议从目标因子轮换中导出无限制的比较双因子模型。本研究的目的是为使用目标旋转作为推导比较模型的方法提供进一步的实证支持。具体来说，我们进行了蒙特卡罗分析，探索 (a) 使用 Schmid-Leiman 正交化来指定可行的初始目标矩阵，以及 (b) 使用 Mplus 中实现的目标旋转来恢复真正的双因子模式矩阵。结果表明，如果项目响应数据符合独立的聚类结构，则可以有效地使用目标旋转来建立合理的比较模型。
Reise, Cook, and Moore proposed a "comparison modeling" approach to assess the distortion in item parameter estimates when a unidimensional item response theory (IRT) model is imposed on multidimensional data. Central to their approach is the comparison of item slope parameter estimates from a unidimensional IRT model (a restricted model), with the item slope parameter estimates from the general factor in an exploratory bifactor IRT model (the unrestricted comparison model). In turn, these authors suggested that the unrestricted comparison bifactor model be derived from a target factor rotation. The goal of this study was to provide further empirical support for the use of target rotations as a method for deriving a comparison model. Specifically, we conducted Monte Carlo analyses exploring (a) the use of the Schmid-Leiman orthogonalization to specify a viable initial target matrix and (b) the recovery of true bifactor pattern matrices using target rotations as implemented in Mplus. Results suggest that to the degree that item response data conform to independent cluster structure, target rotations can be used productively to establish a plausible comparison model.