Abstract
Exploratory factor analysis is a widely used statistical technique in the social sciences. It attempts to identify underlying factors that explain the pattern of correlations within a set of observed variables. A statistical software package is needed to perform the calculations. However, there are some limitations with popular statistical software packages, like SPSS. The R programming language is a free software package for statistical and graphical computing. It offers many packages written by contributors from all over the world and programming resources that allow it to overcome the dialog limitations of SPSS. This paper offers an SPSS dialog written in the R programming language with the help of some packages, so that researchers with little or no knowledge in programming, or those who are accustomed to making their calculations based on statistical dialogs, have more options when applying factor analysis to their data and hence can adopt a better approach when dealing with ordinal, Likert-type data.
Highlights
In SPSS (IBM Corporation 2010a), the only correlation matrix available to perform exploratory factor analysis is the Pearson’s correlation, few rotations are available, parallel analysis and Velicer’s minimum average partial criteria (MAP) to determine the number of factors to retain are not available, and internal reliability is based mainly on Cronbach’s alpha
Exploratory factor analysis is a widely used applied statistical technique in the social sciences that often deals with ordinal data
Some of the limitations of popular statistical software packages can be overcome by this SPSS dialog
Summary
In SPSS (IBM Corporation 2010a), the only correlation matrix available to perform exploratory factor analysis is the Pearson’s correlation, few rotations are available, parallel analysis and Velicer’s minimum average partial criteria (MAP) to determine the number of factors to retain are not available, and internal reliability is based mainly on Cronbach’s alpha. Some implications of software limitations, like those referred, can be seen in many research done by social scientists. The analysis is almost always performed with Pearson’s correlations even when the data is ordinal. These procedures are usually the default option in statistical software packages like SPSS, but it will not always yield the best results. The SPSS dialog is written in the R programming language (R Development Core Team 2011), and requires SPSS 19 (IBM Corporation 2010a), the R plug-in 2.10 (IBM Corporation 2010b) and the following R packages: polycor (Fox 2009), psych (Revelle 2011), GPArotation (Bernaards and Jennrich 2005), nFactors (Raiche and Magis 2011), corpcor (Schaefer, Opgen-Rhein, Zuber, Duarte Silva, and Strimmer 2011) and ICS (Nordhausen, Oja, and Tyler 2008)
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