Factor analysis is a statistical method to explore the relationships among observed variables and identify latent structures. It is crucial in scale development and validity analysis. Key factors affecting the accuracy of factor analysis results include the type of data, sample size, and the number of response categories. While some studies…

Among all, Cronbach's Alpha and McDonald's Omega are commonly used for reliability estimations. The alpha uses inter-item correlations while omega is based on a factor analysis result. This study uses simulated ordinal data sets to test whether the alpha and omega produce different estimates. Their performances were compared according to the…

The main aim of this study is to examine the measurement invariance of the structural equating model constructed on the Awareness and Exposure subscales of Nanoscience and Nanotechnology Awareness Scale (NSTAS) test for three teacher branches, three school types, and two genders by using the covariance structural analysis to test configural and…