Purpose Much research is still needed to compare traditional latent variable models such as confirmatory factor analysis (CFA) to emerging psychometric models such as the Gaussian graphical model (GGM). Previous comparisons of GGM centrality indices …
Theories can be represented as statistical models for empirical testing. There is a vast literature on model selection and multimodel inference that focuses on how to assess which statistical model, and therefore which theory, best fits the available …
This article introduces and demonstrates the application of an R statistical programming environment code for conducting structural equation modeling (SEM) specification searches. The implementation and flexibility of the provided code is …
When the multivariate normality assumption is violated in structural equation modeling, a leading remedy involves estimation via normal theory maximum likelihood with robust corrections to standard errors. We propose that this approach might not be …
A Monte Carlo simulation was conducted to investigate the Type I error rates of several versions of chi-square difference tests for nonnormal data in confirmatory factor analysis (CFA) models. The studied statistics include the uncorrected maximum …
Although much is known about the performance of recent methods for inference and interval estimation for indirect or mediated effects with observed variables, little is known about their performance in latent variable models. This article presents an …
Researchers are often advised to write balanced scales (containing an equal number of positively and negatively worded items) when measuring psychological attributes. This practice is recommended to control for acquiescence bias (ACQ). However, …