Parallel analysis and MBI-HSS:

How many factors? 

Autores: Merino Soto César, Angulo Ramos Marisol

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Mr. Editor: It has been only recently possible to validate the Maslach Burnout Inventory-Human Services Survey (MBI-HSS) among health professionals of Cali, an important step for using this instrument with local empirical support in regard to its reliability of scoring and internal structure. However, two aspects of this analysis can be considered as methodological weaknesses. First, the Cronbach alpha coefficient was calculated for the total group of items, and this is absolutely inappropriate because: a)the authors did not demonstrate empirical support for accomplishing this (e.g., a hierarchical factor analysis), b) the literature indicates that factors in the MBI-HSS are generally independent, a characteristic also reported by Córdoba, et al., and the same authors of the MBI-HSS1) the authors did not report the inter-factor correlations with which an appreciation could have been obtained, at least an heuristic one of the common degree of variance among the factors. Secondly, the authors obtained seven factors in their exploratory factor analysis; this large number of factors seems to be a product of applying a factor retention method that is now consensually seen as inaccurate and little recommended. Specifically, it is known as Kaiser’s rule, Guttman’s rule or simply K1. The problem identified with this method is its over-estimation of the number of factors to be retained, a situation that clearly occurs in the results reported by Cordoba, et al., as reported in their Table 2.

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2014-05-28   |   275 visitas   |   Evalua este artículo 0 valoraciones

Vol. 44 Núm.4. Octubre-Diciembre 2013 Pags. 247-248 Colomb Med 2013; 44(4)