Feuerstahler Leah M
Fordham University.
Multivariate Behav Res. 2022 Jan-Feb;57(1):94-111. doi: 10.1080/00273171.2020.1809980. Epub 2020 Sep 2.
In item response theory, uncertainty associated with estimated item parameters can lead to greater uncertainty in subsequent analyses, such as estimating trait scores for individual examinees. Most existing methods to characterize or correct for item parameter uncertainty implicitly assume that the latent trait continuum is fixed across the posterior distribution of item parameters. However, the latent trait continuum can also be understood as an artifact of the fitted model, such that the location of this continuum is determined with error. In other words, item parameter estimation error implies uncertainty about the location of the metric. This article uses Ramsay's (1996) geometry of the latent trait metric to develop a quantitative measure of , that is, the sampling variability of the latent trait continuum implied by errors in item parameter estimation. Through a series of illustrations, it is clarified how metric stability is related to other item response model evaluation outcomes (e.g., test information, model fit), and how metric stability can be useful in identifying well-determined regions of the latent trait continuum, making sample size recommendations, and selecting a model. Overall, the proposed measure of metric stability provides meaningful and highly interpretable information to aid in item response model evaluation.
在项目反应理论中，与估计的项目参数相关的不确定性可能会导致后续分析中出现更大的不确定性，例如估计个体考生的特质分数。大多数现有的表征或校正项目参数不确定性的方法都隐含地假设潜在特质连续体在项目参数的后验分布中是固定的。然而，潜在特质连续体也可以被理解为拟合模型的一个人为产物，因此这个连续体的位置是有误差地确定的。换句话说，项目参数估计误差意味着关于度量位置的不确定性。本文使用拉姆齐（1996）的潜在特质度量几何学来开发一种对 的定量测量，即由项目参数估计误差所隐含的潜在特质连续体的抽样变异性。通过一系列示例，阐明了度量稳定性如何与其他项目反应模型评估结果（如测试信息、模型拟合）相关，以及度量稳定性如何有助于识别潜在特质连续体的确定良好的区域、提出样本量建议和选择模型。总体而言，所提出的度量稳定性测量提供了有意义且高度可解释的信息，以帮助进行项目反应模型评估。
