title: Exploratory Bi-factor Analysis: The Oblique Case.
abstract: Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford (Psychometrika 47:41-54, 1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler (Psychometrika 76:537-549, 2011) introduced an exploratory form of bi-factor analysis that does not require one to provide an explicit bi-factor structure a priori. They use exploratory factor analysis and a bifactor rotation criterion designed to produce a rotated loading matrix that has an approximate bi-factor structure. Among other things this can be used as an aid in finding an explicit bi-factor structure for use in a confirmatory bi-factor analysis. They considered only orthogonal rotation. The purpose of this paper is to consider oblique rotation and to compare it to orthogonal rotation. Because there are many more oblique rotations of an initial loading matrix than orthogonal rotations, one expects the oblique results to approximate a bi-factor structure better than orthogonal rotations and this is indeed the case. A surprising result arises when oblique bi-factor rotation methods are applied to ideal data.
authors: University of California, Los Angeles, 3400 Purdue Ave., Los Angeles, CA, USA. rij@stat.ucla.edu.
authors: Robert I
authors: RI
authors: Jennrich
authors: University of California, Los Angeles, 3400 Purdue Ave., Los Angeles, CA, USA.
authors: Peter M
authors: PM
authors: Bentler
keywords: bi-factor rotation; general factor; gradient projection algorithms; group factor; oblique rotation; orthogonal rotation