Mixture multigroup factor analysis for unraveling factor loading noninvariance across many groups.
Psychological research often builds on between-group comparisons of (measurements of)
latent variables; for instance, to evaluate cross-cultural differences in neuroticism or …
latent variables; for instance, to evaluate cross-cultural differences in neuroticism or …
Mixture simultaneous factor analysis for capturing differences in latent variables between higher level units of multilevel data
Given multivariate data, many research questions pertain to the covariance structure:
whether and how the variables (eg, personality measures) covary. Exploratory factor …
whether and how the variables (eg, personality measures) covary. Exploratory factor …
Mixture model selection via hierarchical BIC
J Zhao, L Jin, L Shi - Computational Statistics & Data Analysis, 2015 - Elsevier
The Bayesian information criterion (BIC) is one of the most popular criteria for model
selection in finite mixture models. However, it implausibly penalizes the complexity of each …
selection in finite mixture models. However, it implausibly penalizes the complexity of each …
Class enumeration and parameter recovery of growth mixture modeling and second-order growth mixture modeling in the presence of measurement noninvariance …
Population heterogeneity in growth trajectories can be detected with growth mixture
modeling (GMM). It is common that researchers compute composite scores of repeated …
modeling (GMM). It is common that researchers compute composite scores of repeated …
Testing for factor loading differences in mixture simultaneous factor analysis: a Monte Carlo simulation-based perspective
E Geminiani, E Ceulemans… - … Equation Modeling: A …, 2021 - Taylor & Francis
Factor analysis is ubiquitously applied in behavioral sciences for capturing covariances of
observed variables by latent variables (factors). When factor-analyzing data from many …
observed variables by latent variables (factors). When factor-analyzing data from many …