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Abstract:
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Exploratory factor analysis (EFA) is routinely used by researchers to reduce the dimensions of their data, and to form meaningful factors. While there are good guidelines on how to report the results, data visualization tools are rarely used in understanding the results of EFA. Good data visualization, especially in a multivariate framework with ordinal data, makes it easier for people interpret the results of the analysis better. This presentation introduces and demonstrates different data visualization techniques that can be used to illustrate the results of EFA and improve its interpretation. Advantages and disadvantages of each of these techniques are discussed. As EFA is oftentimes used on survey data, apart from visualizations for the results, exploratory data visualization for ordinal variables are also presented. Moreover, these graphical tools can be used for purposes other than EFA. Data visualization and analysis is performed in R using publicly available survey data.
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