Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis
Наилучшие практики разведочного факторного анализа: четыре рекомендации для максимально эффективного проведения анализа
2020-03-09
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exploratory factor analysisfactor extractionfactor rotationnumber of factorssample size
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Abstract (AI)
Exploratory factor analysis (EFA) is a complex, multi-step process. The goal of this paper is to collect, in one article, information that will allow researchers and practitioners to understand the various choices available through popular software packages, and to make decisions about “best practices” in exploratory factor analysis. In particular, this paper provides practical information on making decisions regarding (a) extraction, (b) rotation, (c) the number of factors to interpret, and (d) sample size.
Key Findings
1
It identifies extraction method selection as a key decision requiring consideration when conducting EFA.
2
It provides recommendations for choosing rotation methods and determining the number of factors to interpret.
3
The guidance is designed to clarify options available in popular software packages for researchers and practitioners.
4
The paper addresses sample-size considerations as an essential component of obtaining reliable EFA results.
5
The paper consolidates practical guidance for making informed methodological choices throughout exploratory factor analysis.
Research Object
exploratory factor analysis (EFA)
Research Subject
best-practice decisions regarding factor extraction, rotation, number of factors to interpret, and sample size
Publication Details
Publication Date
2020-03-09
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