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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
Martijn Schoenmakers; Jesper Tijmstra; Jeroen Vermunt; Maria Bolsinova – Educational and Psychological Measurement, 2024
Extreme response style (ERS), the tendency of participants to select extreme item categories regardless of the item content, has frequently been found to decrease the validity of Likert-type questionnaire results. For this reason, various item response theory (IRT) models have been proposed to model ERS and correct for it. Comparisons of these…
Descriptors: Item Response Theory, Response Style (Tests), Models, Likert Scales
Gyamfi, Abraham; Acquaye, Rosemary – Acta Educationis Generalis, 2023
Introduction: Item response theory (IRT) has received much attention in validation of assessment instrument because it allows the estimation of students' ability from any set of the items. Item response theory allows the difficulty and discrimination levels of each item on the test to be estimated. In the framework of IRT, item characteristics are…
Descriptors: Item Response Theory, Models, Test Items, Difficulty Level
Stephanie M. Bell; R. Philip Chalmers; David B. Flora – Educational and Psychological Measurement, 2024
Coefficient omega indices are model-based composite reliability estimates that have become increasingly popular. A coefficient omega index estimates how reliably an observed composite score measures a target construct as represented by a factor in a factor-analysis model; as such, the accuracy of omega estimates is likely to depend on correct…
Descriptors: Influences, Models, Measurement Techniques, Reliability
Justin L. Kern – Journal of Educational and Behavioral Statistics, 2024
Given the frequent presence of slipping and guessing in item responses, models for the inclusion of their effects are highly important. Unfortunately, the most common model for their inclusion, the four-parameter item response theory model, potentially has severe deficiencies related to its possible unidentifiability. With this issue in mind, the…
Descriptors: Item Response Theory, Models, Bayesian Statistics, Generalization
Mahmut Sami Koyuncu; Mehmet Sata – International Journal of Assessment Tools in Education, 2023
The main aim of this study was to introduce the ConQuest program, which is used in the analysis of multivariate and multidimensional data structures, and to show its applications on example data structures. To achieve this goal, a basic research approach was applied. Thus, how to use the ConQuest program and how to prepare the data set for…
Descriptors: Data Analysis, Computer Oriented Programs, Models, Test Items
Maria Bolsinova; Jesper Tijmstra; Leslie Rutkowski; David Rutkowski – Journal of Educational and Behavioral Statistics, 2024
Profile analysis is one of the main tools for studying whether differential item functioning can be related to specific features of test items. While relevant, profile analysis in its current form has two restrictions that limit its usefulness in practice: It assumes that all test items have equal discrimination parameters, and it does not test…
Descriptors: Test Items, Item Analysis, Generalizability Theory, Achievement Tests
Raykov, Tenko – Measurement: Interdisciplinary Research and Perspectives, 2023
This software review discusses the capabilities of Stata to conduct item response theory modeling. The commands needed for fitting the popular one-, two-, and three-parameter logistic models are initially discussed. The procedure for testing the discrimination parameter equality in the one-parameter model is then outlined. The commands for fitting…
Descriptors: Item Response Theory, Models, Comparative Analysis, Item Analysis
Guo, Wenjing; Choi, Youn-Jeng – Educational and Psychological Measurement, 2023
Determining the number of dimensions is extremely important in applying item response theory (IRT) models to data. Traditional and revised parallel analyses have been proposed within the factor analysis framework, and both have shown some promise in assessing dimensionality. However, their performance in the IRT framework has not been…
Descriptors: Item Response Theory, Evaluation Methods, Factor Analysis, Guidelines
Aybek, Eren Can – Journal of Applied Testing Technology, 2021
The study aims to introduce catIRT tools which facilitates researchers' Item Response Theory (IRT) and Computerized Adaptive Testing (CAT) simulations. catIRT tools provides an interface for mirt and catR packages through the shiny package in R. Through this interface, researchers can apply IRT calibration and CAT simulations although they do not…
Descriptors: Item Response Theory, Computer Assisted Testing, Simulation, Models
Laura Laclede – ProQuest LLC, 2023
Because non-cognitive constructs can influence student success in education beyond academic achievement, it is essential that they are reliably conceptualized and measured. Within this context, there are several gaps in the literature related to correctly interpreting the meaning of scale scores when a non-standard response option like I do not…
Descriptors: High School Students, Test Wiseness, Models, Test Items
Alallo, Hajir Mahmood Ibrahim; Mohammed, Aisha; Hamid, Zayad Khalaf; Hassan, Aalaa Yaseen; Kadhim, Qasim Khlaif – International Journal of Language Testing, 2023
Diagnostic classification models (DCMs) have recently become very popular both for research purposes and for real testing endeavors for student assessment. A plethora of DCM models give researchers and practitioners a wide range of options for student diagnosis and classification. One intriguing option that some DCM models offer is the possibility…
Descriptors: Language Tests, Diagnostic Tests, Classification, Clinical Diagnosis
Cronin, Sean D. – ProQuest LLC, 2023
This convergent, parallel, mixed-methods study with qualitative and quantitative content analysis methods was conducted to identify what type of thinking is required by the College and Career Readiness Assessment (CCRA+) by (a) determining the frequency and percentage of questions categorized as higher-level thinking within each cell of Hess'…
Descriptors: Cues, College Readiness, Career Readiness, Test Items
Zhang, Mengxue; Heffernan, Neil; Lan, Andrew – International Educational Data Mining Society, 2023
Automated scoring of student responses to open-ended questions, including short-answer questions, has great potential to scale to a large number of responses. Recent approaches for automated scoring rely on supervised learning, i.e., training classifiers or fine-tuning language models on a small number of responses with human-provided score…
Descriptors: Scoring, Computer Assisted Testing, Mathematics Instruction, Mathematics Tests