Multidimensional Item Response Theory Parameter Estimation With Nonsimple Structure Items
Multidimensional Item Response Theory Parameter Estimation With Nonsimple Structure Items
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DOI：
10.1177/0146621610367787
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发表时间：
2011-01-01
影响因子：
1.2
通讯作者：
Finch, Holmes
中科院分区：
文献类型：
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作者：
Finch, Holmes
多维项目反应理论（MIRT）模型参数的估计可以使用正态-卵形调和分析稳健方法（NOHARM）软件，使用具有未加权最小二乘估计的正态卵形进行。以前的模拟研究表明，这种方法确实可以在各种条件下准确有效地估计项目的区分度和难度。然而，这些研究主要局限于简单结构的情况下，其中每个项目仅与数据背后的潜在特征之一相关联。目前的模拟研究旨在通过比较NOHARM和一维IRT为基础的估计不符合简单结构的项目的难度和区分值，即，与一个以上的潜在特征相关联，以扩展这一早期的工作。感兴趣的结果是在各种条件下参数估计的相对偏差和标准误值，包括非简单结构的存在程度。结果表明，偏差和标准误往往是更大的项目，不符合简单的结构比那些这样做，但这种差异的程度是受因素，如潜在性状之间的相关性，样本量和潜在性状的分布，等等。
Estimation of multidimensional item response theory (MIRT) model parameters can be carried out using the normal ogive with unweighted least squares estimation with the normal-ogive harmonic analysis robust method (NOHARM) software. Previous simulation research has demonstrated that this approach does yield accurate and efficient estimates of item discrimination and difficulty across a variety of conditions. However, these studies have been limited primarily to the case of simple structure, where each item is associated only with one of the latent traits underlying the data. The current simulation study seeks to extend this earlier work by comparing NOHARM and unidimensional IRT-based estimates of difficulty and discrimination values for items that do not conform to simple structure, that is, are associated with more than one latent trait. The outcomes of interest were relative bias and standard error values for parameter estimates under a variety of conditions, including the degree of nonsimple structure present. Results demonstrate that both bias and standard error tended to be larger for items that do not conform to simple structure than for those that do, but that the degree of such differences was influenced by factors such as correlation between the latent traits, sample size and distribution of the latent trait, among others.