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Stefanie A. Wind; Benjamin Lugu; Yurou Wang – International Journal of Testing, 2025
Mokken Scale Analysis (MSA) is a nonparametric approach that offers exploratory tools for understanding the nature of item responses while emphasizing invariance requirements. MSA is often discussed as it relates to Rasch measurement theory, which also emphasizes invariance, but uses parametric models. Researchers who have compared and combined…
Descriptors: Item Response Theory, Scaling, Surveys, Evaluation Methods
Jiaying Xiao; Chun Wang; Gongjun Xu – Grantee Submission, 2024
Accurate item parameters and standard errors (SEs) are crucial for many multidimensional item response theory (MIRT) applications. A recent study proposed the Gaussian Variational Expectation Maximization (GVEM) algorithm to improve computational efficiency and estimation accuracy (Cho et al., 2021). However, the SE estimation procedure has yet to…
Descriptors: Error of Measurement, Models, Evaluation Methods, Item Analysis
Tong Wu; Stella Y. Kim; Carl Westine; Michelle Boyer – Journal of Educational Measurement, 2025
While significant attention has been given to test equating to ensure score comparability, limited research has explored equating methods for rater-mediated assessments, where human raters inherently introduce error. If not properly addressed, these errors can undermine score interchangeability and test validity. This study proposes an equating…
Descriptors: Item Response Theory, Evaluators, Error of Measurement, Test Validity
Klauth, Bo – ProQuest LLC, 2023
In conducting confirmatory factor analysis with ordered response items, the literature suggests that when the number of responses is five and item skewness (IS) is approximately normal, researchers can employ maximum likelihood with robust standard errors (MLR). However, MLR can yield biased factor loadings (FL) and FL standard errors (FLSE) when…
Descriptors: Item Response Theory, Evaluation Methods, Factor Analysis, Error of Measurement
Han, Yuting; Zhang, Jihong; Jiang, Zhehan; Shi, Dexin – Educational and Psychological Measurement, 2023
In the literature of modern psychometric modeling, mostly related to item response theory (IRT), the fit of model is evaluated through known indices, such as X[superscript 2], M2, and root mean square error of approximation (RMSEA) for absolute assessments as well as Akaike information criterion (AIC), consistent AIC (CAIC), and Bayesian…
Descriptors: Goodness of Fit, Psychometrics, Error of Measurement, Item Response Theory
Stefanie A. Wind; Yangmeng Xu – Educational Assessment, 2024
We explored three approaches to resolving or re-scoring constructed-response items in mixed-format assessments: rater agreement, person fit, and targeted double scoring (TDS). We used a simulation study to consider how the three approaches impact the psychometric properties of student achievement estimates, with an emphasis on person fit. We found…
Descriptors: Interrater Reliability, Error of Measurement, Evaluation Methods, Examiners
Yuanfang Liu; Mark H. C. Lai; Ben Kelcey – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Measurement invariance holds when a latent construct is measured in the same way across different levels of background variables (continuous or categorical) while controlling for the true value of that construct. Using Monte Carlo simulation, this paper compares the multiple indicators, multiple causes (MIMIC) model and MIMIC-interaction to a…
Descriptors: Classification, Accuracy, Error of Measurement, Correlation
Xue Zhang; Chun Wang – Grantee Submission, 2022
Item-level fit analysis not only serves as a complementary check to global fit analysis, it is also essential in scale development because the fit results will guide item revision and/or deletion (Liu & Maydeu-Olivares, 2014). During data collection, missing response data may likely happen due to various reasons. Chi-square-based item fit…
Descriptors: Goodness of Fit, Item Response Theory, Scores, Test Length
Peabody, Michael R. – Applied Measurement in Education, 2020
The purpose of the current article is to introduce the equating and evaluation methods used in this special issue. Although a comprehensive review of all existing models and methodologies would be impractical given the format, a brief introduction to some of the more popular models will be provided. A brief discussion of the conditions required…
Descriptors: Evaluation Methods, Equated Scores, Sample Size, Item Response Theory
Hosseinzadeh, Mostafa – ProQuest LLC, 2021
In real-world situations, multidimensional data may appear on large-scale tests or attitudinal surveys. A simple structure, multidimensional model may be used to evaluate the items, ignoring the cross-loading of some items on the secondary dimension. The purpose of this study was to investigate the influence of structure complexity magnitude of…
Descriptors: Item Response Theory, Models, Simulation, Evaluation Methods
Wang, Chun; Xu, Gongjun; Zhang, Xue – Grantee Submission, 2019
When latent variables are used as outcomes in regression analysis, a common approach that is used to solve the ignored measurement error issue is to take a multilevel perspective on item response modeling (IRT). Although recent computational advancement allow efficient and accurate estimation of multilevel IRT models, we argue that a two-stage…
Descriptors: Error of Measurement, Item Response Theory, Regression (Statistics), Evaluation Methods
Barrett, Michelle D.; van der Linden, Wim J. – Journal of Educational Measurement, 2017
Linking functions adjust for differences between identifiability restrictions used in different instances of the estimation of item response model parameters. These adjustments are necessary when results from those instances are to be compared. As linking functions are derived from estimated item response model parameters, parameter estimation…
Descriptors: Item Response Theory, Error of Measurement, Programming, Evaluation Methods
Park, Sung Eun; Ahn, Soyeon; Zopluoglu, Cengiz – Educational and Psychological Measurement, 2021
This study presents a new approach to synthesizing differential item functioning (DIF) effect size: First, using correlation matrices from each study, we perform a multigroup confirmatory factor analysis (MGCFA) that examines measurement invariance of a test item between two subgroups (i.e., focal and reference groups). Then we synthesize, across…
Descriptors: Item Analysis, Effect Size, Difficulty Level, Monte Carlo Methods
Hyunsuk Han – ProQuest LLC, 2018
In Huggins-Manley & Han (2017), it was shown that WLSMV global model fit indices used in structural equating modeling practice are sensitive to person parameter estimate RMSE and item difficulty parameter estimate RMSE that results from local dependence in 2-PL IRT models, particularly when conditioning on number of test items and sample size.…
Descriptors: Models, Statistical Analysis, Item Response Theory, Evaluation Methods
Gulsah Gurkan – ProQuest LLC, 2021
Secondary analyses of international large-scale assessments (ILSA) commonly characterize relationships between variables of interest using correlations. However, the accuracy of correlation estimates is impaired by artefacts such as measurement error and clustering. Despite advancements in methodology, conventional correlation estimates or…
Descriptors: Secondary School Students, Achievement Tests, International Assessment, Foreign Countries