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使用适宜性测量统计量拟合拉施模型。

Fitting Rasch model using appropriateness measure statistics.

作者信息

López Pina José Antonio, Hidalgo Montesinos M Dolores

机构信息

University of Murcia, Spain.

出版信息

Span J Psychol. 2005 May;8(1):100-10. doi: 10.1017/s113874160000500x.

Abstract

In this paper, the distributional properties and power rates of the Lz, Eci2z, and Eci4z statistics when they are used as item fit statistics were explored. The results were compared to t-transformation of Outfit and Infit mean square. Four sample sizes were selected: 100, 250, 500, and 1000 examinees. The abilities were uniform and normal with mean 0 and standard deviation 1, and uniform and normal with mean -1 and standard deviation 1. The pseudo-guessing parameter was fixed at .25. Two ranges of difficulty parameters were selected: +/- 1 logits and +/- 2 logits. Two test lengths were selected: 15 and 30 items. The results showed important differences between the T-infit, T-outfit, Lz, Eci2z, and Eci4z statistics. The T-oufit, T-infit, and Lz statistics showed poor standardization with estimated parameters because their distributional properties were not close to the expected values. However, the Eci2z and Eci4z statistics showed satisfactory standardization on all conditions. Further, the power rates of Eci2z and Eci4z were 5% to 10% higher than the power rates of Lz, T-outfit, and T-infit to detect items that do not fit Rasch model.

摘要

本文探讨了Lz、Eci2z和Eci4z统计量用作项目拟合统计量时的分布特性和功效率。将结果与装备和内拟合均方的t变换进行了比较。选择了四个样本量:100、250、500和1000名考生。能力分布为均值为0、标准差为1的均匀正态分布,以及均值为-1、标准差为1的均匀正态分布。伪猜测参数固定为0.25。选择了两个难度参数范围:±1对数单位和±2对数单位。选择了两种测验长度:15题和30题。结果显示,T内拟合、T装备、Lz、Eci2z和Eci4z统计量之间存在重要差异。T装备、T内拟合和Lz统计量在估计参数时标准化较差,因为它们的分布特性与预期值不接近。然而,Eci2z和Eci4z统计量在所有条件下均显示出令人满意的标准化。此外,Eci2z和Eci4z的功效率比Lz、T装备和T内拟合检测不符合拉施模型项目的功效率高5%至10%。

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