Gonzalez-Roma Vicente, Hernandez Ana, Gomez-Benito Juana
Multivariate Behav Res. 2006 Mar 1;41(1):29-53. doi: 10.1207/s15327906mbr4101_3.
In this simulation study, we investigate the power and Type I error rate of a procedure based on the mean and covariance structure analysis (MACS) model in detecting differential item functioning (DIF) of graded response items with five response categories. The following factors were manipulated: type of DIF (uniform and non-uniform), DIF magnitude (low, medium and large), equality/inequality of latent trait distributions, sample size (100, 200, 400, and 800) and equality or inequality of the sample sizes across groups. The simulated test was made up of 10 items, of which only 1 contained DIF. One hundred replications were generated for each simulated condition. Results indicate that the MACS-based procedure showed acceptable power levels (≥ .70) for detecting medium-sized uniform and non-uniform DIF, when both groups' sample sizes were as low as 200/200 and 400/200, respectively. Power increased as sample sizes and DIF magnitude increased. The analyzed procedure tended to better control for its Type I error when both groups' sizes and latent trait distribution were equal across groups and when magnitude of DIF and sample size were small.
在这项模拟研究中，我们基于均值和协方差结构分析（MACS）模型，研究一种程序在检测具有五个反应类别的等级反应项目的差异项目功能（DIF）时的功效和I型错误率。我们操纵了以下因素：DIF的类型（一致和非一致）、DIF大小（低、中、高）、潜在特质分布的相等性/不相等性、样本量（100、200、400和800）以及各组样本量的相等或不相等。模拟测试由10个项目组成，其中只有1个项目存在DIF。针对每个模拟条件生成了100次重复。结果表明，当两组样本量分别低至200/200和400/200时，基于MACS的程序在检测中等大小的一致和非一致DIF时显示出可接受的功效水平（≥.70）。功效随着样本量和DIF大小的增加而提高。当两组的大小和潜在特质分布在组间相等，且DIF大小和样本量较小时，所分析的程序倾向于更好地控制其I型错误。
