Comportamiento de las correlaciones producto-momento y tetracórica-policórica en escalas ordinalesun estudio de simulación

  1. Martínez-Abad, Fernando 1
  2. Rodríguez-Conde, María José 1
  1. 1 Universidad de Salamanca
    info

    Universidad de Salamanca

    Salamanca, España

    ROR https://ror.org/02f40zc51

Revista:
Relieve: Revista ELectrónica de Investigación y EValuación Educativa

ISSN: 1134-4032

Any de publicació: 2017

Volum: 23

Número: 2

Tipus: Article

DOI: 10.7203/RELIEVE.23.2.9476 DIALNET GOOGLE SCHOLAR lock_openAccés obert editor

Altres publicacions en: Relieve: Revista ELectrónica de Investigación y EValuación Educativa

Resum

The statistical multivariate analysis of Likert response scales, given their widespread use, is a controversial issue in the scientific community, mainly from the specification of the problem of measurement. This work aims to study various conditions of these ordinal scales affect the calculation of the product-moment and tetrachoric-polychoric correlation coefficients. For this purpose, a simulation study was applied in which 90 databases with 10 items each were generated. In the estimation of the databases, the following variables were controlled: number of response categories, symmetrical or asymmetric distributions of data, sample size and level of relationship between items. Thus, 90 matrices (10x10) were obtained which included the difference between the product-moment and tetrachoric-polychoric correlations. The graphical and variance analysis show how the product-moment correlation coefficient significantly underestimates the relationship between variables mainly when the number of response categories of the ordinal scale is small and the relationship between the variables is large. On the other hand, the statistical estimation of both coefficients is very similar when the starting relationship between pairs of variables is small and/or when the number of response options of the variables is greater than 5. The study concludes by making a recommendation to the applied researcher on the most appropriate correlation coefficient depending on the type of data available. Finally, the results are discussed from the previous studies, which reach some similar conclusions.

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