Publication Date
In 2025 | 7 |
Since 2024 | 33 |
Since 2021 (last 5 years) | 75 |
Since 2016 (last 10 years) | 196 |
Since 2006 (last 20 years) | 513 |
Descriptor
Item Response Theory | 748 |
Simulation | 748 |
Test Items | 307 |
Models | 245 |
Comparative Analysis | 153 |
Computation | 133 |
Sample Size | 113 |
Evaluation Methods | 112 |
Error of Measurement | 111 |
Computer Assisted Testing | 107 |
Scores | 99 |
More ▼ |
Source
Author
Wang, Wen-Chung | 19 |
Cohen, Allan S. | 17 |
Cai, Li | 14 |
Glas, Cees A. W. | 13 |
Woods, Carol M. | 13 |
Meijer, Rob R. | 12 |
Sinharay, Sandip | 12 |
Sijtsma, Klaas | 10 |
Bolt, Daniel M. | 9 |
Chang, Hua-Hua | 8 |
DeMars, Christine E. | 8 |
More ▼ |
Publication Type
Education Level
Audience
Researchers | 6 |
Practitioners | 2 |
Location
Netherlands | 4 |
Taiwan | 3 |
Turkey | 3 |
Austria | 2 |
Canada | 2 |
China | 2 |
Denmark | 2 |
Florida | 2 |
Germany | 2 |
North Carolina | 2 |
Tunisia | 2 |
More ▼ |
Laws, Policies, & Programs
No Child Left Behind Act 2001 | 2 |
Assessments and Surveys
What Works Clearinghouse Rating
Zeyuan Jing – ProQuest LLC, 2023
This dissertation presents a comprehensive review of the evolution of DIF analysis within educational measurement from the 1980s to the present. The review elucidates the concept of DIF, particularly emphasizing the crucial role of grouping for exhibiting DIF. Then, the dissertation introduces an innovative modification to the newly developed…
Descriptors: Item Response Theory, Algorithms, Measurement, Test Bias
Ye Ma; Deborah J. Harris – Educational Measurement: Issues and Practice, 2025
Item position effect (IPE) refers to situations where an item performs differently when it is administered in different positions on a test. The majority of previous research studies have focused on investigating IPE under linear testing. There is a lack of IPE research under adaptive testing. In addition, the existence of IPE might violate Item…
Descriptors: Computer Assisted Testing, Adaptive Testing, Item Response Theory, Test Items
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
Stefanie A. Wind; Benjamin Lugu – Applied Measurement in Education, 2024
Researchers who use measurement models for evaluation purposes often select models with stringent requirements, such as Rasch models, which are parametric. Mokken Scale Analysis (MSA) offers a theory-driven nonparametric modeling approach that may be more appropriate for some measurement applications. Researchers have discussed using MSA as a…
Descriptors: Item Response Theory, Data Analysis, Simulation, Nonparametric Statistics
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
Yue Liu; Zhen Li; Hongyun Liu; Xiaofeng You – Applied Measurement in Education, 2024
Low test-taking effort of examinees has been considered a source of construct-irrelevant variance in item response modeling, leading to serious consequences on parameter estimation. This study aims to investigate how non-effortful response (NER) influences the estimation of item and person parameters in item-pool scale linking (IPSL) and whether…
Descriptors: Item Response Theory, Computation, Simulation, Responses
Yamaguchi, Kazuhiro; Zhang, Jihong – Journal of Educational Measurement, 2023
This study proposed Gibbs sampling algorithms for variable selection in a latent regression model under a unidimensional two-parameter logistic item response theory model. Three types of shrinkage priors were employed to obtain shrinkage estimates: double-exponential (i.e., Laplace), horseshoe, and horseshoe+ priors. These shrinkage priors were…
Descriptors: Algorithms, Simulation, Mathematics Achievement, Bayesian Statistics
Chia-Lin Tsai; Stefanie Wind; Samantha Estrada – Measurement: Interdisciplinary Research and Perspectives, 2025
Researchers who work with ordinal rating scales sometimes encounter situations where the scale categories do not function in the intended or expected way. For example, participants' use of scale categories may result in an empirical difficulty ordering for the categories that does not match what was intended. Likewise, the level of distinction…
Descriptors: Rating Scales, Item Response Theory, Psychometrics, Self Efficacy

Marcelo Andrade da Silva; A. Corinne Huggins-Manley; Jorge Luis Bazan; Amber Benedict – Grantee Submission, 2024
A Q-matrix is a binary matrix that defines the relationship between items and latent variables and is widely used in diagnostic classification models (DCMs), and can also be adopted in multidimensional item response theory (MIRT) models. The construction process of the Q-matrix is typically carried out by experts in the subject area of the items…
Descriptors: Q Methodology, Matrices, Item Response Theory, Educational Assessment
Marcelo Andrade da Silva; A. Corinne Huggins-Manley; Jorge Luis Bazán; Amber Benedict – Applied Measurement in Education, 2024
A Q-matrix is a binary matrix that defines the relationship between items and latent variables and is widely used in diagnostic classification models (DCMs), and can also be adopted in multidimensional item response theory (MIRT) models. The construction process of the Q-matrix is typically carried out by experts in the subject area of the items…
Descriptors: Q Methodology, Matrices, Item Response Theory, Educational Assessment
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; Dubravka Svetina Valdivia – Educational and Psychological Measurement, 2024
Identifying items with differential item functioning (DIF) in an assessment is a crucial step for achieving equitable measurement. One critical issue that has not been fully addressed with existing studies is how DIF items can be detected when data are multilevel. In the present study, we introduced a Lord's Wald X[superscript 2] test-based…
Descriptors: Item Analysis, Item Response Theory, Algorithms, Accuracy
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