Test Essay

10029 Words Jul 28th, 2014 41 Pages
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Email: jkanglim@unimelb.edu.au Office: Room 1110 Redmond Barry Building Website: http://jeromyanglim.googlepages.com/ Appointments: For appointments regarding course or with the application of statistics to your thesis, just send me an email

Cluster Analysis & Factor Analysis
325-711 Research Methods 2007 Lecturer: Jeromy Anglim
“Of particular concern is the fairly routine use of a variation of exploratory factor analysis wherein the researcher uses principal components analysis (PCA), retains components with eigenvalues greater than 1 and uses varimax rotation, a bundle of procedures affectionately termed “Little Jiffy” …”
Preacher, K. J., MacCallum, R. C. (2003). Repairing Tom Swift's Electric Factor Analysis Machine.
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F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. ( 2006). Multivariate Data Analysis (6th ed). New York: Macmillion Publishing Company. Chapter 8: Cluster Analysis

• Preacher, K. J., MacCallum, R. C. (2003). Repairing Tom Swift's Electric Factor Analysis Machine. Understanding Statistics, 2(1), 13-43. • Comrey, A. L. (1988). Factor analytic methods of scale development in personality and clinical psychology. Journal of Consulting and Clinical Psychology, 56(5), 754-761.

Tabachnick & Fiddel (1996) The style of this chapter is typical of Tabachnick & Fiddel. It is quite comprehensive and provides many citations to other authors regarding particular techniques. It goes through the issues and assumptions thoroughly. It provides advice on write-up and computer output interpretation. It even has the underlying matrix algebra, which most of us tend to skip over, but is there if you want to get a deeper understanding. There is a more recent version of the book that might also be worth checking out. Hair et al (2006) The chapter is an excellent place to start for understanding factor analysis. The examples are firmly grounded in a business context. The pedagogical strategies for explaining the ideas of cluster analysis are excellent. Preacher & MacCallum (2003) This article calls on researchers to think about the choices inherent in carrying out a principal components analysis/factor analysis. It criticises the conventional use of what is called

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