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Adrian Quintero; Emmanuel Lesaffre; Geert Verbeke – Journal of Educational and Behavioral Statistics, 2024
Bayesian methods to infer model dimensionality in factor analysis generally assume a lower triangular structure for the factor loadings matrix. Consequently, the ordering of the outcomes influences the results. Therefore, we propose a method to infer model dimensionality without imposing any prior restriction on the loadings matrix. Our approach…
Descriptors: Bayesian Statistics, Factor Analysis, Factor Structure, Sampling
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Fujimoto, Ken A.; Neugebauer, Sabina R. – Educational and Psychological Measurement, 2020
Although item response theory (IRT) models such as the bifactor, two-tier, and between-item-dimensionality IRT models have been devised to confirm complex dimensional structures in educational and psychological data, they can be challenging to use in practice. The reason is that these models are multidimensional IRT (MIRT) models and thus are…
Descriptors: Bayesian Statistics, Item Response Theory, Sample Size, Factor Structure
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Fujimoto, Ken A. – Educational and Psychological Measurement, 2019
Advancements in item response theory (IRT) have led to models for dual dependence, which control for cluster and method effects during a psychometric analysis. Currently, however, this class of models does not include one that controls for when the method effects stem from two method sources in which one source functions differently across the…
Descriptors: Bayesian Statistics, Item Response Theory, Psychometrics, Models
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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
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Hayashi, Kentaro; Sen, Pranab K. – Educational and Psychological Measurement, 2002
Implemented a Bayesian factor analysis model to formulate estimators of the hyper-parameters. Simulation results lead to the proposal of new bias-corrected estimates of factor loadings. (SLD)
Descriptors: Bayesian Statistics, Estimation (Mathematics), Factor Structure, Simulation
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Shi, Jian-Qing; Lee, Sik-Yum – Psychometrika, 1997
Explores posterior analysis in estimating factor score in a confirmatory factor analysis model with polytomous, censored or truncated data, and studies the accuracy of Bayesian estimates through simulation. Results support these Bayesian estimates for statistical inference. (SLD)
Descriptors: Bayesian Statistics, Estimation (Mathematics), Factor Structure, Scores
Urry, Vern W. – 1971
Bayesian estimation procedures are summarized and numerically illustrated by means of simulation methods. Procedures of data generation for simulation purposes are also delineated and computationally demonstrated. The logistic model basic to the Bayesian estimation procedures is shown to be explicit with respect to the probability distribution…
Descriptors: Achievement Tests, Adaptive Testing, Bayesian Statistics, Computer Programs