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Chunhua Cao; Benjamin Lugu; Jujia Li – Structural Equation Modeling: A Multidisciplinary Journal, 2024
This study examined the false positive (FP) rates and sensitivity of Bayesian fit indices to structural misspecification in Bayesian structural equation modeling. The impact of measurement quality, sample size, model size, the magnitude of misspecified path effect, and the choice or prior on the performance of the fit indices was also…
Descriptors: Structural Equation Models, Bayesian Statistics, Measurement, 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

W. Jake Thompson – Grantee Submission, 2024
Diagnostic classification models (DCMs) are psychometric models that can be used to estimate the presence or absence of psychological traits, or proficiency on fine-grained skills. Critical to the use of any psychometric model in practice, including DCMs, is an evaluation of model fit. Traditionally, DCMs have been estimated with maximum…
Descriptors: Bayesian Statistics, Classification, Psychometrics, Goodness of Fit
Zhang, Xue; Wang, Chun; Tao, Jian – Grantee Submission, 2018
Testing item-level fit is important in scale development to guide item revision/deletion. Many item-level fit indices have been proposed in literature, yet none of them were directly applicable to an important family of models, namely, the higher order item response theory (HO-IRT) models. In this study, chi-square-based fit indices (i.e., Yen's…
Descriptors: Item Response Theory, Models, Test Items, Goodness of Fit
Sideridis, Georgios D.; Tsaousis, Ioannis; Alamri, Abeer A. – Educational and Psychological Measurement, 2020
The main thesis of the present study is to use the Bayesian structural equation modeling (BSEM) methodology of establishing approximate measurement invariance (A-MI) using data from a national examination in Saudi Arabia as an alternative to not meeting strong invariance criteria. Instead, we illustrate how to account for the absence of…
Descriptors: Bayesian Statistics, Structural Equation Models, Foreign Countries, Error of Measurement
Kim, Weon H. – ProQuest LLC, 2017
The purpose of the present study is to apply the item response theory (IRT) and testlet response theory (TRT) models to a reading comprehension test. This study applied the TRT models and the traditional IRT model to a seventh-grade reading comprehension test (n = 8,815) with eight testlets. These three models were compared to determine the best…
Descriptors: Item Response Theory, Test Items, Correlation, Reading Tests
Liang, Longjuan; Browne, Michael W. – Journal of Educational and Behavioral Statistics, 2015
If standard two-parameter item response functions are employed in the analysis of a test with some newly constructed items, it can be expected that, for some items, the item response function (IRF) will not fit the data well. This lack of fit can also occur when standard IRFs are fitted to personality or psychopathology items. When investigating…
Descriptors: Item Response Theory, Statistical Analysis, Goodness of Fit, Bayesian Statistics
Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2015
Person-fit assessment may help the researcher to obtain additional information regarding the answering behavior of persons. Although several researchers examined person fit, there is a lack of research on person-fit assessment for mixed-format tests. In this article, the lz statistic and the ?2 statistic, both of which have been used for tests…
Descriptors: Test Format, Goodness of Fit, Item Response Theory, Bayesian Statistics
Lee, HwaYoung; Beretvas, S. Natasha – Educational and Psychological Measurement, 2014
Conventional differential item functioning (DIF) detection methods (e.g., the Mantel-Haenszel test) can be used to detect DIF only across observed groups, such as gender or ethnicity. However, research has found that DIF is not typically fully explained by an observed variable. True sources of DIF may include unobserved, latent variables, such as…
Descriptors: Item Analysis, Factor Structure, Bayesian Statistics, Goodness of Fit