No matter how strong the theoretical infrastructure of a study is, if the measurement instruments do not have the necessary psychometric qualities, there will be a question of trust in interpreting the findings, and it will be inevitable to make wrong decisions with the results. One of the important steps in scale development/adaptation studies is…

Meta-analytic structural equation modeling (MASEM) involves fitting models to a common population correlation matrix that is estimated on the basis of correlation coefficients that are reported by a number of independent studies. MASEM typically consist of two stages. The method that has been found to perform best in terms of statistical…

Rubin and Thayer ("Psychometrika," 47:69-76, 1982) proposed the EM algorithm for exploratory and confirmatory maximum likelihood factor analysis. In this paper, we prove the following fact: the EM algorithm always gives a proper solution with positive unique variances and factor correlations with absolute values that do not exceed one,…

Numerous procedures have been suggested for determining the number of factors to retain in factor analysis. However, previous studies have focused on comparing methods using normal data sets. This study had two phases. The first phase explored the Kaiser method, Scree test, Bartlett's chi-square test, Minimum Average Partial (1976&2000),…

Estimation techniques for generating the covariance matrix for two new tests and an existing test without the necessity of any examinee having to take two complete tests is presented. An application of these techniques to linear, observed-score, test equating is presented. (Author/JKS)

Confirmatory maximum likelihood factor analysis determined how accurately each of several hypothesized combinations of first-order and higher-order factors reflecting creativity in the social intelligence of 192 high school students described the covariation in selected submatrixes from the total correlation matrix originally analyzed. Results…

In traditional factor analysis, the variance-covariance matrix or the correlation matrix has often been a form of inputting data. In contrast, in Bayesian factor analysis, the entire data set is typically required to compute the posterior estimates, such as Bayes factor loadings and Bayes unique variances. We propose a simple method for computing…

A correlation matrix of 21 structure-of-intellect (SOI) tests taken by 204 Marine officers at a military base in Southern California, which was intended to reflect aptitudes for military leadership, was reanalyzed through exploratory factor analysis and confirmatory maximum likelihood factor analysis. Higher order factors appeared to have…

This study examined the effect of type of correlation matrix on the robustness of LISREL maximum likelihood and unweighted least squares structural parameter estimates for models with categorical manifest variables. Two types of correlation matrices were analyzed; one containing Pearson product-moment correlations and one containing tetrachoric,…