# Exploratory Factor Analysis – Exercises

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.