Estimating Classification Accuracy and Consistency Indices for Multiple Measures with the Simple Structure MIRT Model

IF 1.4 4区 心理学 Q3 PSYCHOLOGY, APPLIED
Seohee Park, Kyung Yong Kim, Won-Chan Lee
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引用次数: 1

Abstract

Multiple measures, such as multiple content domains or multiple types of performance, are used in various testing programs to classify examinees for screening or selection. Despite the popular usages of multiple measures, there is little research on classification consistency and accuracy of multiple measures. Accordingly, this study introduces an approach to estimate classification consistency and accuracy indices for multiple measures under four possible decision rules: (1) complementary, (2) conjunctive, (3) compensatory, and (4) pairwise combinations of the three. The current study uses the IRT-recursive-based approach with the simple-structure multidimensional IRT model (SS-MIRT) to estimate the classification consistency and accuracy for multiple measures. Theoretical formulations of the four decision rules with a binary decision (Pass/Fail) are presented. The estimation procedures are illustrated using an empirical data example based on SS-MIRT. In addition, this study applies the estimation procedures to the unidimensional IRT (UIRT) context, considering that UIRT is practically used more. This application shows that the proposed procedure of classification consistency and accuracy could be used with a UIRT model for individual measures as an alternative method of SS-MIRT.

用简单结构MIRT模型估计多个测度的分类精度和一致性指标
多种测试方法,如多种内容领域或多种类型的表现,在各种测试程序中被用于对考生进行筛选或选择。尽管多测度的用法比较普遍,但对多测度的分类一致性和准确性的研究却很少。基于此,本文提出了一种基于四种可能的决策规则(1)互补、(2)连接、(3)补偿和(4)三者的两两组合来估计多度量的分类一致性和准确度指标的方法。本研究采用基于IRT递归的方法,结合简单结构多维IRT模型(SS-MIRT)来估计多测量的分类一致性和准确性。给出了四种二元决策规则(通过/不通过)的理论表达式。利用基于SS-MIRT的经验数据示例说明了估计过程。此外,考虑到一维IRT的实际应用较多,本研究将估计过程应用于一维IRT情境。该应用表明,所提出的分类一致性和准确性的程序可以与单个测量的irt模型一起使用,作为SS-MIRT的替代方法。
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来源期刊
CiteScore
2.30
自引率
7.70%
发文量
46
期刊介绍: The Journal of Educational Measurement (JEM) publishes original measurement research, provides reviews of measurement publications, and reports on innovative measurement applications. The topics addressed will interest those concerned with the practice of measurement in field settings, as well as be of interest to measurement theorists. In addition to presenting new contributions to measurement theory and practice, JEM also serves as a vehicle for improving educational measurement applications in a variety of settings.
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