Factor Analysis

Marko Sarstedt and Erik Mooi
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Marko Sarstedt: Otto-von-Guericke-Universität
Erik Mooi: University of Melbourne

Chapter 8 in A Concise Guide to Market Research, 2014, pp 235-272 from Springer

Abstract: Learning Objectives After reading this chapter, you should understand: The principles of exploratory and confirmatory factor analysis. The difference between principal components analysis and principal axis factoring. Key terms such as EigenvaluesEigenvalues, communality, factor loadings, and factor scores. How to determine whether data are suitable for carrying out an exploratory factor analysis. How to interpret SPSS factor analysis output. The principles of reliability analysisreliability analysis and how to carry it out in SPSS. The basic idea behind structural equation modeling. structural equation modeling.

Keywords: Anti-image; Bartlett’s test of sphericity; Communality; Cronbach’s Alpha; Eigenvalue; Exploratory and confirmatory factor analysis; Factor loadings; Factor scores; Kaiser criterion; Kaiser–Meyer–Olkin (KMO) criterion; Measure of sampling adequacy (MSA); Orthogonal and oblique rotation; Partial least squares; Principal axis factoring; Principal components analysis; Reliability analysis; Scree plot; Structural equation modeling; Varimax and direct oblimin rotation (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sptchp:978-3-642-53965-7_8

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DOI: 10.1007/978-3-642-53965-7_8

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