Uploaded May 2023 | Updated September 2026, 2 weeks ago
This video provides a demonstration of how to use the EFA.dimensions package with RStudio to make a determination of the number of factors that may explain the intercorrelations among a set of measured variables. I use an example and data from journals.plos.org/plosone/article?id=10.1371/journal.pone.0173295 .
A copy of the Excel data file can be downloaded here: docs.google.com/file/d/1Q8H43VIWGR11YrMqQ4pUMsDis9datNYj/view
A copy of the Powerpoint slides I reference in the video can be accessed here:
docs.google.com/file/d/11jMov52G7q04CMqtFrQglbqw8nlG61Kx/view
A text file containing the code used in this video can be downloaded here:
drive.google.com/file/d/1b9UJ8XNcgKvN_YfTeBaLoYBWuI3hFt4Q/view
Link to EFA.dimensions documentation:
cran.r-project.org/web/packages/EFA.dimensions/EFA.dimensions.pdf
Be sure to check out my blog, where I discuss the issue of over- and under-factoring:
mikesquanthub.blogspot.com/2023/05/Possible consequences of over- versus under-factoring.html
This video provides a demonstration of how to use the EFA.dimensions package with RStudio to make a determination of the number of factors that may explain the intercorrelations among a set of measured variables. I use an example and data from journals.plos.org/plosone/article?id=10.1371/journal.pone.0173295 .
A copy of the Excel data file can be downloaded here: docs.google.com/file/d/1Q8H43VIWGR11YrMqQ4pUMsDis9datNYj/view
A copy of the Powerpoint slides I reference in the video can be accessed here:
docs.google.com/file/d/11jMov52G7q04CMqtFrQglbqw8nlG61Kx/view
A text file containing the code used in this video can be downloaded here:
drive.google.com/file/d/1b9UJ8XNcgKvN_YfTeBaLoYBWuI3hFt4Q/view
Link to EFA.dimensions documentation:
cran.r-project.org/web/packages/EFA.dimensions/EFA.dimensions.pdf
Be sure to check out my blog, where I discuss the issue of over- and under-factoring:
mikesquanthub.blogspot.com/2023/05/Possible consequences of over- versus under-factoring.html
