A test of construct validity of the work meaning inventory

The purpose of this study was to test the eight factors model and a high order factor structure of the Work Meaning Inventory(WMI) developed by Tak et al.(2015) and with a sample of employees. Data were obtained from 1,000 employees using online survey. Results of exploratory factor analyses confirmed the original 8 factors of the WMI, confirming the construct validity of the WMI. Also results of high-order factor analyses showed that the three higher order factors(make a living, growth opportunity, self-actualization) were obtained. Finally, the implications, limitations, and future studies are discussed.

Validation of the Kenny Music Performance Anxiety Inventory (K-MPAI): A cross-cultural confirmation of its factorial structure

This research investigated whether music performance anxiety (MPA) can be theoretically understood as a unidimensional construct, and whether the factorial structure is robust across different populations of musicians with different levels of expertise. K-MPAI scores were obtained from 455 Peruvian tertiary music students (mean age = 21.19 years, SD = 3.13, range = 18–40 years) and 368 Australian professional orchestral musicians (mean age = 42.07 years, SD = 10.21, range = 18–68 years). A high order exploratory factor analysis with the Schmid-Leiman solution was performed on the K-MPAI items. Unweighted Least Squares extraction method and optimal implementation of parallel analysis revealed one high order factor and two first order factors for both samples. High Cronbach’s and ordinal alpha levels for items belonging to each first order and high order factor in both samples were also obtained. Structural similarities between the two samples and an invariance analysis signified a comparable structure and conceptual interpretation of K-MPAI scores in both populations. The factorial structure obtained supported a unidimensional interpretation of the construct of MPA. First order level interpretations are also possible and have been demonstrated to be clinically useful.

Modeling the Spearman's Hypothesis using MGCFA - The Woodcock-Johnson data

There has been a good deal of research on Spearman’s hypothesis with regard to Black-White differences in tests of cognitive ability. Most of the research has relied on Jensen’s Method of Correlated Vectors (Jensen, 1998). This method, however, is incapable of rigorously testing competing models that do not involve group differences in g (Dolan, 2000, Dolan & Hamaker, 2001). The purpose of the present paper is to test Spearman’s hypothesis using Multi-Group Confirmatory Factor Analysis applied to three waves of Woodcock-Johnson standardization data. First, using Jensen’s MCV, it is found, for all three standardization waves, that there is a Jensen effect, i.e., positive correlation between the subtests’ g-loadings and the Black-White differences. Secondly, while measurement invariance (MI) was generally found to hold, results from MGCFA using either the high-order-factor or the bi-factor model approach could not reliably confirm that the Spearman’s model fits better than the contra-Spearman’s model. Tentative explanations are provided.