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…

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…

A number of psychometricians have suggested that parallel analysis (PA) tends to yield more accurate results in determining the number of factors in comparison with other statistical methods. Nevertheless, all too often PA can suggest an incorrect number of factors, particularly in statistically unfavorable conditions (e.g., small sample sizes and…

This study evaluated the validity of the Michigan English Test (MET) Listening Section by investigating its underlying factor structure and the replicability of its factor structure across multiple test forms. Data from 3255 test takers across four forms of the MET Listening Section were used. To investigate the factor structure, each form was…

This Monte Carlo simulation study aimed to investigate confirmatory factor analysis (CFA) estimation methods under different conditions, such as sample size, distribution of indicators, test length, average factor loading, and factor structure. Binary data were generated to compare the performance of maximum likelihood (ML), mean and variance…

When item scores are ordered categorical, categorical omega can be computed based on the parameter estimates from a factor analysis model using frequentist estimators such as diagonally weighted least squares. When the sample size is relatively small and thresholds are different across items, using diagonally weighted least squares can yield a…

Bayesian structural equation modeling (BSEM) was used to investigate the latent structure of the Differential Ability Scales-Second Edition core battery using the standardization sample normative data for ages 7-17. Results revealed plausibility of a three-factor model, consistent with publisher theory, expressed as either a higher-order (HO) or a…

Standardized teaching observation protocols have become increasingly popular in evaluating teaching in recent years. One of such protocols that has gained substantial interest from researchers and practitioners is the Classroom Assessment Scoring System-Secondary (CLASSS). According to the developer, CLASS-S has three domains of teacher-student…

The Mathematical Resilience Scale measures students' attitudes toward studying mathematics, using three correlated factors: Value, Struggle, and Growth. The Mathematical Resilience Scale was developed and validated using exploratory and confirmatory factor analyses across three samples. Results provide a new approach to gauge the likelihood of…

Bayesian factor analysis (BFA) assumes the normal distribution of the current sample conditional on the parameters. Practical data in social and behavioral sciences typically have significant skewness and kurtosis. If the normality assumption is not attainable, the posterior analysis will be inaccurate, although the BFA depends less on the current…

A Bayesian procedure is given for estimation in unrestricted common factor analysis. A choice of the form of the prior distribution is justified. The procedure achieves its objective of avoiding inadmissible estimates of unique variances, and is reasonably insensitive to certain variations in the shape of the prior distribution. (Author/BJG)

Researchers have been limited in their ability to examine multiple constructs simultaneously due to the constraints imposed by traditional statistical methods. The most notable limitations include the need for a relatively large sample size while restricting the variables to a relatively small number. The application of a newly discovered…

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…