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Multilevel mixture factor models for the evaluation of educational programs’ effectiveness

  • Roberta Varriale
  • Caterina Giusti
Conference paper
Part of the Contributions to Statistics book series (CONTRIB.STAT.)

Abstract

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.

Keywords

Latent Variable Bayesian Information Criterion Factor Model Latent Class Analysis Cultural Interest 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Physica-Verlag Heidelberg 2009

Authors and Affiliations

  1. 1.Department of Methodology and StatisticsTilburg UniversityTilburgThe Netherlands
  2. 2.Department of Statistics “G. Parenti”University of FlorenceFlorenceItaly
  3. 3.Department of Statistics and Mathematics Applied to EconomicsUniversity of PisaPisaItaly

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