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首页> 外文期刊>SAGE Open >Assessing Testlet Effect, Impact, Differential Testlet, and Item Functioning Using Cross-Classified Multilevel Measurement Modeling:
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Assessing Testlet Effect, Impact, Differential Testlet, and Item Functioning Using Cross-Classified Multilevel Measurement Modeling:

机译：使用交叉分类的多级测量模型评估睾丸效应，影响，差异睾丸和项目功能：

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The present study used the two-level testlet response model (MMMT-2) to assess impact, differential item functioning (DIF), and differential testlet functioning (DTLF) in a reading comprehension test. The data came from 21,641 applicants into English Mastersa?? programs at Iranian state universities. Testlet effects were estimated, and items and testlets that were functioning differentially for test takers of different genders and majors were identified. Also parameter estimates obtained under MMMT-2 and those obtained under the two-level hierarchical generalized linear model (HGLM-2) were compared. The results indicated that ability estimates obtained under the two models were significantly different at the lower and upper ends of the ability distribution. In addition, it was found that ignoring local item dependence (LID) would result in overestimation of the precision of the ability estimates. As for the difficulty of the items, the estimates obtained under the two models were almost the same, but standard errors were significantly different.
机译：本研究使用二级睾丸反应模型（MMMT-2）来评估阅读理解测试中的影响力，差异项功能（DIF）和差异睾丸功能（DTLF）。数据来自21,641位申请者进入English Mastersa？伊朗国立大学的课程。估计了睾丸的影响，并确定了不同性别和专业的应试者的功能和项目差异。还比较了在MMMT-2下获得的参数估计和在两级分层广义线性模型（HGLM-2）下获得的参数估计。结果表明，在两种模型下获得的能力估计值在能力分布的下端和上端显着不同。此外，还发现忽略局部项依赖（LID）会导致对能力估计精度的高估。至于项目的难度，在两个模型下获得的估计值几乎相同，但是标准误却有很大差异。

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