A Comparison of Methods for Determining the Number of Factors to Retain with Exploratory Factor Analysis of Dichotomous Data

Exploratory factor analysis (EFA) is a very widely used statistical procedure in the social and behavioral sciences. This technique features in validity studies, as well as investigations of latent structure underlying observed measurements. A primary aspect of using EFA is determining the number of...
Ausführliche Beschreibung

Exploratory factor analysis (EFA) is a very widely used statistical procedure in the social and behavioral sciences. This technique features in validity studies, as well as investigations of latent structure underlying observed measurements. A primary aspect of using EFA is determining the number of factors to retain. In addition to theoretical considerations, a variety of statistical tools have been developed and recommended for use in assisting researchers with respect to factor retention. Some research has been conducted to investigate the accuracy of these methods in the case of continuous factor indicators. The purpose of the current simulation study was to extend this earlier work to situations in which the indicator variables are dichotomous, as with questionnaire or test items. Results of this study revealed that an approach based on the combined results of the empirical Kaiser criterion, comparative data, and Hull methods, as well as Gorsuch’s CNG scree plot test by itself, all yielded accurate results with respect to the number of factors to retain. Implications for practice are discussed. Ausführliche Beschreibung