Exploratory Factor Analysis – Exercises

June 14, 2017

(This article was first published on R-exercises, and kindly contributed to R-bloggers)

This set of exercises is about exploratory factor analysis. We shall use some basic features of psych package. For quick introduction to exploratory factor analysis and psych package, we recommend this short “how to” guide.

You can download the dataset here. The data is fictitious.

Answers to the exercises are available here.

If you have different solution, feel free to post it.

Exercise 1

Load the data, install the packages psych and GPArotation which we will use in the following exercises, and load it. Describe the data.

Exercise 2

Using the parallel analysis, determine the number of factors.

Exercise 3

Determine the number of factors using Very Simple Structure method.

Exercise 4

Based on normality test, is the Maximum Likelihood factoring method proper, or is OLS/Minres better? (Tip: Maximum Likelihood method requires normal distribution.)

Exercise 5

Using oblimin rotation, 5 factors and factoring method from the previous exercise, find the factor solution. Print loadings table with cut off at 0.3.

Exercise 6

Plot factors loadings.

Exercise 7

Plot structure diagram.

Exercise 8

Find the higher-order factor model with five factors plus general factor.

Exercise 9

Find the bifactor solution.

Exercise 10

Reduce the number of dimensions using hierarchical clustering analysis.

To leave a comment for the author, please follow the link and comment on their blog: R-exercises.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.


Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)