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Sohee Kim; Ki Lynn Cole – International Journal of Testing, 2025
This study conducted a comprehensive comparison of Item Response Theory (IRT) linking methods applied to a bifactor model, examining their performance on both multiple choice (MC) and mixed format tests within the common item nonequivalent group design framework. Four distinct multidimensional IRT linking approaches were explored, consisting of…
Descriptors: Item Response Theory, Comparative Analysis, Models, Item Analysis
Xiaowen Liu – International Journal of Testing, 2024
Differential item functioning (DIF) often arises from multiple sources. Within the context of multidimensional item response theory, this study examined DIF items with varying secondary dimensions using the three DIF methods: SIBTEST, Mantel-Haenszel, and logistic regression. The effect of the number of secondary dimensions on DIF detection rates…
Descriptors: Item Analysis, Test Items, Item Response Theory, Correlation
Furlan, Luis Alberto; Cassady, Jerrell C.; Perez, Edgardo Raul – International Journal of Testing, 2009
A new Spanish version of the Cognitive Test Anxiety Scale (CTAS) was created to be used explicitly with Argentinean university students. The scale was translated and verified through blind back translation and given to a large sample of students majoring in psychology or chemistry (N = 752). Exploratory Factor Analysis (N = 376) showed an internal…
Descriptors: Factor Structure, Cognitive Tests, Measures (Individuals), Factor Analysis
Rupp, Andre A. – International Journal of Testing, 2003
Item response theory (IRT) has become one of the most popular scoring frameworks for measurement data. IRT models are used frequently in computerized adaptive testing, cognitively diagnostic assessment, and test equating. This article reviews two of the most popular software packages for IRT model estimation, BILOG-MG (Zimowski, Muraki, Mislevy, &…
Descriptors: Test Items, Adaptive Testing, Item Response Theory, Computer Software
Dirkzwager, Arie – International Journal of Testing, 2003
The crux in psychometrics is how to estimate the probability that a respondent answers an item correctly on one occasion out of many. Under the current testing paradigm this probability is estimated using all kinds of statistical techniques and mathematical modeling. Multiple evaluation is a new testing paradigm using the person's own personal…
Descriptors: Psychometrics, Probability, Models, Measurement