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Roy Levy; Daniel McNeish – Journal of Educational and Behavioral Statistics, 2025
Research in education and behavioral sciences often involves the use of latent variable models that are related to indicators, as well as related to covariates or outcomes. Such models are subject to interpretational confounding, which occurs when fitting the model with covariates or outcomes alters the results for the measurement model. This has…
Descriptors: Models, Statistical Analysis, Measurement, Data Interpretation
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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
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Ming-Chi Tseng – Structural Equation Modeling: A Multidisciplinary Journal, 2025
This study aims to estimate the latent interaction effect in the CLPM model through a two-step multiple imputation analysis. The estimation of within x within and between x within latent interaction under the CLPM model framework is compared between the one-step Bayesian LMS method and the two-step multiple imputation analysis through a simulation…
Descriptors: Guidelines, Bayesian Statistics, Self Esteem, Depression (Psychology)
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Kazuhiro Yamaguchi – Journal of Educational and Behavioral Statistics, 2025
This study proposes a Bayesian method for diagnostic classification models (DCMs) for a partially known Q-matrix setting between exploratory and confirmatory DCMs. This Q-matrix setting is practical and useful because test experts have pre-knowledge of the Q-matrix but cannot readily specify it completely. The proposed method employs priors for…
Descriptors: Models, Classification, Bayesian Statistics, Evaluation Methods
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Minju Kim; Adena Schachner – Developmental Science, 2025
Listening to music activates representations of movement and social agents. Why? We test whether causal reasoning plays a role, and find that from childhood, people can intuitively reason about how musical sounds were generated, inferring the events and agents that caused the sounds. In Experiment 1 (N = 120, pre-registered), 6-year-old children…
Descriptors: Causal Models, Abstract Reasoning, Thinking Skills, Music
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Na Shan; Ping-Feng Xu – Journal of Educational and Behavioral Statistics, 2025
The detection of differential item functioning (DIF) is important in psychological and behavioral sciences. Standard DIF detection methods perform an item-by-item test iteratively, often assuming that all items except the one under investigation are DIF-free. This article proposes a Bayesian adaptive Lasso method to detect DIF in graded response…
Descriptors: Bayesian Statistics, Item Response Theory, Adolescents, Longitudinal Studies