Multilevel mixture factor models for the evaluation of educational programs’ effectiveness
Factor models aim at explaining the associations among observed random variables in terms of fewer unobserved random variables, called common factors. When data have a hierarchical structure, multilevel mixture factor models are a powerful and flexible tool useful to correctly take into account the correlation between first-level units due to the data structure, and to evaluate the presence of latent sub-populations of units with some typical profile at different levels of the analysis.
KeywordsLatent Variable Bayesian Information Criterion Factor Model Latent Class Analysis Cultural Interest
Unable to display preview. Download preview PDF.