Polychoric versus Pearson correlations in exploratory and confirmatory factor analysis of ordinal variables |
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Authors: | Francisco Pablo Holgado–Tello Salvador Chacón–Moscoso Isabel Barbero–García Enrique Vila–Abad |
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Institution: | 1.Dpto. Metodología de las Ciencias del Comportamiento, Facultad de Psicología,UNED,Madrid,Spain;2.Metodología de las Ciencias del Comportamiento, Facultad de Psicología,Universidad de Sevilla,Sevilla,Spain |
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Abstract: | Given that the use of Likert scales is increasingly common in the field of social research it is necessary to determine which
methodology is the most suitable for analysing the data obtained; although, given the categorization of these scales, the
results should be treated as ordinal data it is often the case that they are analysed using techniques designed for cardinal
measures. One of the most widely used techniques for studying the construct validity of data is factor analysis, whether exploratory
or confirmatory, and this method uses correlation matrices (generally Pearson) to obtain factor solutions. In this context,
and by means of simulation studies, we aim to illustrate the advantages of using polychoric rather than Pearson correlations,
taking into account that the latter require quantitative variables measured in intervals, and that the relationship between
these variables has to be monotonic. The results show that the solutions obtained using polychoric correlations provide a
more accurate reproduction of the measurement model used to generate the data. |
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Keywords: | |
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