A brief introduction to hierarchical classes (HICLAS) models

Authors

  • Iwin Leenen

DOI:

https://doi.org/10.1016/j.riem.2015.09.003

Keywords:

Clases jerárquicas, Clustering, Datos binarios, Modelos componenciales, Hierarchical classes, Binary data, Componential models

Abstract

This article presents a nontechnical introduction to the family of hierarchical classes (HICLAS) models. The original HICLAS model, proposed by De Boeck and Rosenberg in 1988, is suited for the analysis of a binary data matrix; that is, it analyses a two-way table with values equal to 0 or 1. Unlike other classification methods, the output of a HICLAS analysis includes (a) two hierarchical classifications, one for the ‘‘objects’’ (the table’s rows) and another for the ‘‘attributes’’ (the columns), and (b) an association of these classifications from which it is possible to predict (or reconstruct) the value in each cell of the table. The advantages of HICLAS models are illustrated with examples in the field of medical education, with an explanation of the different steps in the application of the model, as well as special emphasis on the interpretation of the results.

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Author Biography

Iwin Leenen

Instituto Nacional para la Evaluación de la Educación, México D.F., México

Published

01-10-2015

How to Cite

Leenen, I. (2015). A brief introduction to hierarchical classes (HICLAS) models. Medical Education Research Journal, 4(16), 242–251. https://doi.org/10.1016/j.riem.2015.09.003

Issue

Section

Medical education research methodology

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