使用MULTILOG对部分信用模型进行参数恢复。

Journal of outcome measurement Pub Date : 1997-01-01
S W Choi, K F Cook, B G Dodd
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引用次数: 0

摘要

本文利用MULTILOG计算机程序对部分信用模型的参数恢复进行了研究。研究的因素是样本量和项目数量参数,这是通过系统地改变每个项目的步骤数和项目数量来操纵的。研究结果表明,当考虑到每个项目的步骤数时,样本大小与被估计的项目参数数的比率作为“经验法则”可以是一个更完整的指导。在所有条件下都可以获得准确的能力估计,即使样本量只有250人。然而,对于步长值的估计,需要更加谨慎。准确估计具有更多类别的项目的步长值需要更大的样本量来估计给定数量的总参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parameter recovery for the partial credit model using MULTILOG.

This study investigated parameter recovery for the partial credit model using the MULTILOG computer program. Factors studied were the sample size and the number of item parameters, which were manipulated by systematically varying the number of steps per item and the number of items. The findings suggest that the ratio of sample size to number of item parameters being estimated as a "rule of thumb" can be a more complete guideline when the number of steps per item is taken into account. Accurate estimation of ability can be obtained across all conditions, even with sample sizes as small as 250. With regard to estimation of step values, however, more caution is warranted. Accurate estimation of the step values of items which have more categories requires larger sample sizes for a given number of total parameters to be estimated.

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