TITLE

EIGENVECTORSPACE: THE MISSING CONCEPT IN EXPLORATORY FACTOR ANALYSIS

AUTHOR(S)
Wenbin Guo
PUB. DATE
September 2008
SOURCE
Review of Business Research;2008, Vol. 8 Issue 4, p151
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
While there has been a well-developed solution procedure for exploratory factor analysis (EFA) in that factor retention and factor rotation have been consistently used for data summarization, the theory behind its use has not been explicitly defined and fine-tuned to give its users a strong sense of certainty and a perceptual advantage. The key word 'factor' used in current literature is critically confusing. Sometimes, factors are identified by an eigenvalue-eigenvector procedure, and at other times factors are defined as underlying patterns of variable association. The concepts and mathematical treatments behind the two kinds of factors are not consistent as well. As a result, many survey researchers avoid EFA and instead use Confirmatory Factor Analysis (CFA) for data exploration. To give a strong theoretical backing for EFA applications, this paper introduces a new concept of 'eigenvectorspace' into the logical framework of exploratory factor analysis.
ACCESSION #
35601379

 

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