Source: Dissertation Abstracts International, Volume: 59-10, Section: B, page: 5428.

A new index based on the conditional covariance of item scores given a latent variable is defined and investigated to assess dimensionality in educational and psychological test data. This index successfully detects the test dimensionality in both identifying the number of dimensions present in...

Heterogeneity in measurement model parameters across known groups can be modeled and tested using multigroup confirmatory factor analysis (CFA). When it is not reasonable to assume that parameters are homogeneous for all observations in a manifest group, mixture CFA models are appropriate....

Measuring continuous change or growth in individual students' academic abilities over time currently uses several statistical models or transformations to move from data representing a student's correct or incorrect responses on individual test items to inferences about the form and quantity of...

The study describes the various alternatives to the between-subjects ANOVA F test that have been performing reasonably well in the literature under different experimental conditions of sample sizes, variance ratios or nonnormality. Drawing from structural equation modeling (SEM), the robust...

If data exhibit a dimensional structure more complex than what is assumed, key conditional independence assumptions of the hypothesized model do not hold. The current work pursues posterior predictive model checking, a flexible family of Bayesian model checking procedures, as a tool for...

Mixture modeling is an increasingly popular analysis in applied research settings. Confirmatory factor mixture modeling can be used to test for the presence of multiple populations that differ on one or more parameters of a factor model in a sample lacking a priori information about population...