Optimal Scores: An Alternative to Parametric Item Response Theory and Sum Scores
Optimal Scores: An Alternative to Parametric Item Response Theory and Sum Scores
复制标题
最佳分数：参数项目响应理论和总分数的替代方案
DOI：
10.1007/s11336-018-9639-4
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发表时间：
2018
期刊：
影响因子：
3
通讯作者：
Juan
中科院分区：
文献类型：
--
作者：
M. Wiberg;J. Ramsay;Juan
本文的目的是从最优分数的角度讨论非参数项目反应理论分数，作为参数项目反应理论分数和总和分数的替代方案。最优分数利用性能和项目影响之间的相互作用，这在大多数测试数据中是显而易见的。模拟实验结果补充了支持最优评分的理论论点，对测试数据的分析表明，为了达到相同的准确性水平，和分测试需要比最优评分测试更长。因为最优评分是建立在一个非参数程序上的，它也提供了一个灵活的选择来估计项目特征曲线，可以适合那些不适合项目反应理论模型的项目。
The aim of this paper is to discuss nonparametric item response theory scores in terms of optimal scores as an alternative to parametric item response theory scores and sum scores. Optimal scores take advantage of the interaction between performance and item impact that is evident in most testing data. The theoretical arguments in favor of optimal scoring are supplemented with the results from simulation experiments, and the analysis of test data suggests that sum-scored tests would need to be longer than an optimally scored test in order to attain the same level of accuracy. Because optimal scoring is built on a nonparametric procedure, it also offers a flexible alternative for estimating item characteristic curves that can fit items that do not show good fit to item response theory models.