# rotation

### Four Common Misconceptions in Exploratory Factor Analysis

June 5th, 2018 by

Today, I would like to briefly describe four misconceptions that I feel are commonly perceived by novice researchers in Exploratory Factor Analysis:

### Misconception 1: The choice between component and common factor extraction procedures is not so important.

In Principal Component Analysis, a set of variables is transformed into a smaller set of linear composites known as components. This method of analysis is essentially a method for data reduction.

### In Factor Analysis, How Do We Decide Whether to Have Rotated or Unrotated Factors?

January 20th, 2017 by

I recently gave a free webinar on Principal Component Analysis. We had almost 300 researchers attend and didn’t get through all the questions. This is part of a series of answers to those questions.

If you missed it, you can get the webinar recording here.

### Question: How do we decide whether to have rotated or unrotated factors?

When you retain only one factor in a solution, then rotation is irrelevant. In fact, most software won’t even print out rotated coefficients and they’re pretty meaningless in that situation.

But if you retain two or more factors, you need to rotate.

Unrotated factors are pretty difficult to interpret in that situation. (more…)

### Member Training: Exploratory Factor Analysis

March 1st, 2013 by

Many variables we want to measure just can’t be directly measured with a single variable. Instead you have to combine a set of variables into a single index.

But how do you determine which variables to combine and how best to combine them?

Exploratory Factor Analysis.

EFA is a method for finding a measurement for one or more unmeasurable (latent) variables from a set of related observed variables. It is especially useful for scale construction.

In this webinar, you will learn through three examples an overview of EFA, including:

• The five steps to conducting an EFA
• Key concepts like rotation
• Factor scores
• The importance of interpretability

Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and part of the Stat’s Amore Trainings Series. Each Stat’s Amore Training is approximately 90 minutes long.

Not a Member? Join!