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Factor analysis is a dimensionality reduction latent variable technique which replaces inter-correlating variables with a smaller number of continuous latent variables called factors. The factors are believed to be responsible for the inter-correlations. [For confirmatory factor analysis, please use the tag 'confirmatory-factor'. Also, the term "factor" of factor analysis should not be confused with "factor" as categorical predictor of a regression/ANOVA.]

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factor analysis, eigenvalues vs. squared factor loadings vs. scree plot eigenvalues [duplicate]

I performed an exploratory factor analysis for a data set with 8 variables. KMO and Bartlett's test I also carried out to make sure the data are eligible for this examination. Scree plot I prepared a …
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1 vote
1 answer
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Discrepancies in explained variance depending on the print method

While performing an exploratory factor analysis, I want to see the explained variance by the factors. It is straightforward and I printed the output of the fa() method. One can get the same summary ta …
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exploratory factor analysis, oblique rotation, variance explained

The update part of the question I posted on stackoverflow that was migrated to stackexchange but a full in-depth answer was posted by Prof. William Revelle, maintainer and writer of the psych package. …
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exploratory factor analysis, oblique rotation, variance explained

The question how to compute the variance explained by a factor model obtained through exploratory factors analysis pops up from time to time. A summary with many possibilities is here: Calculating var …
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