Abstract
The fundamental mathematical model of Thurstone's common factor analysis is reviewed. The basic covariance matrices of maximum likelihood factor analysis (MLFA) and alpha factor analysis (AFA) are presented. Putting aside the principles on which they are based, these two methods are compared in terms of a number of computational and scaling contrasts following from the application of their respective developments
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
