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Ö. Emre C. Alagöz; Thorsten Meiser – Educational and Psychological Measurement, 2024
To improve the validity of self-report measures, researchers should control for response style (RS) effects, which can be achieved with IRTree models. A traditional IRTree model considers a response as a combination of distinct decision-making processes, where the substantive trait affects the decision on response direction, while decisions about…
Descriptors: Item Response Theory, Validity, Self Evaluation (Individuals), Decision Making
Hanke Vermeiren; Abe D. Hofman; Maria Bolsinova – International Educational Data Mining Society, 2025
The traditional Elo rating system (ERS), widely used as a student model in adaptive learning systems, assumes unidimensionality (i.e., all items measure a single ability or skill), limiting its ability to handle multidimensional data common in educational contexts. In response, several multidimensional extensions of the Elo rating system have been…
Descriptors: Item Response Theory, Models, Comparative Analysis, Algorithms
Jean-Paul Fox – Journal of Educational and Behavioral Statistics, 2025
Popular item response theory (IRT) models are considered complex, mainly due to the inclusion of a random factor variable (latent variable). The random factor variable represents the incidental parameter problem since the number of parameters increases when including data of new persons. Therefore, IRT models require a specific estimation method…
Descriptors: Sample Size, Item Response Theory, Accuracy, Bayesian Statistics
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
Huang, Hung-Yu – Educational and Psychological Measurement, 2023
The forced-choice (FC) item formats used for noncognitive tests typically develop a set of response options that measure different traits and instruct respondents to make judgments among these options in terms of their preference to control the response biases that are commonly observed in normative tests. Diagnostic classification models (DCMs)…
Descriptors: Test Items, Classification, Bayesian Statistics, Decision Making
Aiman Mohammad Freihat; Omar Saleh Bani Yassin – Educational Process: International Journal, 2025
Background/purpose: This study aimed to reveal the accuracy of estimation of multiple-choice test items parameters following the models of the item-response theory in measurement. Materials/methods: The researchers depended on the measurement accuracy indicators, which express the absolute difference between the estimated and actual values of the…
Descriptors: Accuracy, Computation, Multiple Choice Tests, Test Items
Hung, Su-Pin; Huang, Hung-Yu – Journal of Educational and Behavioral Statistics, 2022
To address response style or bias in rating scales, forced-choice items are often used to request that respondents rank their attitudes or preferences among a limited set of options. The rating scales used by raters to render judgments on ratees' performance also contribute to rater bias or errors; consequently, forced-choice items have recently…
Descriptors: Evaluation Methods, Rating Scales, Item Analysis, Preferences
Boris Forthmann; Benjamin Goecke; Roger E. Beaty – Creativity Research Journal, 2025
Human ratings are ubiquitous in creativity research. Yet, the process of rating responses to creativity tasks -- typically several hundred or thousands of responses, per rater -- is often time-consuming and expensive. Planned missing data designs, where raters only rate a subset of the total number of responses, have been recently proposed as one…
Descriptors: Creativity, Research, Researchers, Research Methodology
Sijia Huang; Seungwon Chung; Carl F. Falk – Journal of Educational Measurement, 2024
In this study, we introduced a cross-classified multidimensional nominal response model (CC-MNRM) to account for various response styles (RS) in the presence of cross-classified data. The proposed model allows slopes to vary across items and can explore impacts of observed covariates on latent constructs. We applied a recently developed variant of…
Descriptors: Response Style (Tests), Classification, Data, Models
Zsuzsa Bakk – Structural Equation Modeling: A Multidisciplinary Journal, 2024
A standard assumption of latent class (LC) analysis is conditional independence, that is the items of the LC are independent of the covariates given the LCs. Several approaches have been proposed for identifying violations of this assumption. The recently proposed likelihood ratio approach is compared to residual statistics (bivariate residuals…
Descriptors: Goodness of Fit, Error of Measurement, Comparative Analysis, Models
Sweeney, Sandra M.; Sinharay, Sandip; Johnson, Matthew S.; Steinhauer, Eric W. – Educational Measurement: Issues and Practice, 2022
The focus of this paper is on the empirical relationship between item difficulty and item discrimination. Two studies--an empirical investigation and a simulation study--were conducted to examine the association between item difficulty and item discrimination under classical test theory and item response theory (IRT), and the effects of the…
Descriptors: Correlation, Item Response Theory, Item Analysis, Difficulty Level
Hoang V. Nguyen; Niels G. Waller – Educational and Psychological Measurement, 2024
We conducted an extensive Monte Carlo study of factor-rotation local solutions (LS) in multidimensional, two-parameter logistic (M2PL) item response models. In this study, we simulated more than 19,200 data sets that were drawn from 96 model conditions and performed more than 7.6 million rotations to examine the influence of (a) slope parameter…
Descriptors: Monte Carlo Methods, Item Response Theory, Correlation, Error of Measurement
Joakim Wallmark; James O. Ramsay; Juan Li; Marie Wiberg – Journal of Educational and Behavioral Statistics, 2024
Item response theory (IRT) models the relationship between the possible scores on a test item against a test taker's attainment of the latent trait that the item is intended to measure. In this study, we compare two models for tests with polytomously scored items: the optimal scoring (OS) model, a nonparametric IRT model based on the principles of…
Descriptors: Item Response Theory, Test Items, Models, Scoring
William R. Nugent – Measurement: Interdisciplinary Research and Perspectives, 2024
Symmetry considerations are important in science, and Group Theory is a theory of symmetry. Classical Measurement Theory is the most used measurement theory in the social and behavioral sciences. In this article, the author uses Matrix Lie (Lee) group theory to formulate a measurement model. Symmetry is defined and illustrated using symmetries of…
Descriptors: Item Response Theory, Measurement Techniques, Models, Simulation
Wind, Stefanie A.; Ge, Yuan – Measurement: Interdisciplinary Research and Perspectives, 2023
In selected-response assessments such as attitude surveys with Likert-type rating scales, examinees often select from rating scale categories to reflect their locations on a construct. Researchers have observed that some examinees exhibit "response styles," which are systematic patterns of responses in which examinees are more likely to…
Descriptors: Goodness of Fit, Responses, Likert Scales, Models

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