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Direct linkTenko 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
A. M. Sadek; Fahad Al-Muhlaki – Measurement: Interdisciplinary Research and Perspectives, 2024
In this study, the accuracy of the artificial neural network (ANN) was assessed considering the uncertainties associated with the randomness of the data and the lack of learning. The Monte-Carlo algorithm was applied to simulate the randomness of the input variables and evaluate the output distribution. It has been shown that under certain…
Descriptors: Monte Carlo Methods, Accuracy, Artificial Intelligence, Guidelines
