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Tenko Raykov; George Marcoulides; Randall Schumacker – Measurement: Interdisciplinary Research and Perspectives, 2024
An application of Bayesian factor analysis for evaluation of scale reliability is discussed, which is developed within the framework of latent variable modeling. The method permits direct point and interval estimation of the reliability coefficient of multiple-component measuring instruments using Bayesian inference. The approach allows also point…
Descriptors: Reliability, Bayesian Statistics, Measurement Techniques, Computer Software
Tenko Raykov; George Marcoulides; James Anthony; Natalja Menold – Measurement: Interdisciplinary Research and Perspectives, 2024
A Bayesian statistics-based approach is discussed that can be used for direct evaluation of the popular Cronbach's coefficient alpha as an internal consistency index for multiple-component measuring instruments, as well as for testing its identity to scale reliability. The method represents an application of confirmatory factor analysis within the…
Descriptors: Reliability, Factor Analysis, Bayesian Statistics, Measurement Techniques
Chantelle Gray – Educational Philosophy and Theory, 2025
In contemporary societies, the processes of transindividuation by which knowledges are transformed into cycles and rhythms of metastability have been dramatically short-circuited. In turn, this has provoked the spiritual misery and pseudo-fabulations so prevalent all around us, including our educational contexts. For Stiegler, this is nothing…
Descriptors: Educational Philosophy, Electronic Learning, Automation, Educational Theories
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
James Ohisei Uanhoro – Structural Equation Modeling: A Multidisciplinary Journal, 2024
We present a method for Bayesian structural equation modeling of sample correlation matrices as correlation structures. The method transforms the sample correlation matrix to an unbounded vector using the matrix logarithm function. Bayesian inference about the unbounded vector is performed assuming a multivariate-normal likelihood, with a mean…
Descriptors: Bayesian Statistics, Structural Equation Models, Correlation, Monte Carlo Methods
Caspar J. Van Lissa; Eli-Boaz Clapper; Rebecca Kuiper – Research Synthesis Methods, 2024
The product Bayes factor (PBF) synthesizes evidence for an informative hypothesis across heterogeneous replication studies. It can be used when fixed- or random effects meta-analysis fall short. For example, when effect sizes are incomparable and cannot be pooled, or when studies diverge significantly in the populations, study designs, and…
Descriptors: Hypothesis Testing, Evaluation Methods, Replication (Evaluation), Sample Size
Teck Kiang Tan – Practical Assessment, Research & Evaluation, 2024
The procedures of carrying out factorial invariance to validate a construct were well developed to ensure the reliability of the construct that can be used across groups for comparison and analysis, yet mainly restricted to the frequentist approach. This motivates an update to incorporate the growing Bayesian approach for carrying out the Bayesian…
Descriptors: Bayesian Statistics, Factor Analysis, Programming Languages, Reliability
Giuseppe Arena; Joris Mulder; Roger Th. A. J. Leenders – Sociological Methods & Research, 2024
In relational event networks, the tendency for actors to interact with each other depends greatly on the past interactions between the actors in a social network. Both the volume of past interactions and the time that has elapsed since the past interactions affect the actors' decision-making to interact with other actors in the network. Recently…
Descriptors: Bayesian Statistics, Social Networks, Memory, Decision Making