Factor Analysis of Scales Composed of Binary Items: Illustration with the Maudsley Obsessional Compulsive Inventory

It is well known that traditional factor analytic methods are designed for use with continuous data, and suboptimal for items with 2 response options (i.e., binary items). Nevertheless, traditional methods have been employed in all previous assessment of the dimensionality of the Maudsley Obsessional Compulsive Inventory (MOCI), a true/false measure of obsessive–compulsive symptoms ( R. J. Hodgson &; S. Rachman, 1977). The aim of this paper is to illustrate 2 techniques that are more suitable for factor-analyzing binary items than traditional methods, through application to the MOCI (n = 1,080). Computer files for use with the TESTFACT (D. Wilson, R. L. Wood, &; R. Gibbons, 1991 ) and Mplus (Muthén &; Muthén, 1998) computer programs are provided. Results from an inappropriately applied principal axis factor analysis are presented for comparison, and factor structures, loadings, and interfactor correlations are compared across methods.