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# Factor Analysis in R

4.1+
12 reviews

Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.

4 Hours13 Videos45 Exercises

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## Discover Factor Analysis in R

The world is full of unobservable variables that can't be directly measured. You might be interested in a construct such as math ability, personality traits, or workplace climate. When investigating constructs like these, it's critically important to have a model that matches your theories and data.

This course will help you understand dimensionality and show you how to conduct exploratory and confirmatory factor analyses.

## Learn to Use Exploratory Factor Analysis and Confirmatory Factor Analysis

You’ll start by getting to grips with exploratory factor analysis (EFA), learning how to view and visualize factor loadings, interpret factor scores, and view and test correlations.

Once you’re familiar with single-factor EFA, you’ll move on to multidimensional data, looking at calculating eigenvalues, creating screen plots, and more. Next, you’ll discover confirmatory factor analysis (CFAs), learning how to create syntax from EFA results and theory.

The final chapter looks at EFAs vs CFAs, giving examples of both. You’ll also learn how to improve your model and measure when using them.

Develop, Refine, and Share Your Measures

## With these statistical techniques in your toolkit, you'll be able to develop, refine, and share your measures. These analyses are foundational for diverse fields, including psychology, education, political science, economics, and linguistics."

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1. 1

### Evaluating your measure with factor analysis

Free

In Chapter 1, you will learn how to conduct an EFA to examine the statistical properties of a measure designed around one construct.

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Introduction to Exploratory Factor Analysis (EFA)
50 xp
Starting out with a unidimensional EFA
100 xp
100 xp
Interpreting individuals' factor scores
100 xp
Overview of the measure development process
50 xp
100 xp
100 xp
Comparing the halves of your dataset
100 xp
Measure features: correlations and reliability
50 xp
Viewing and testing correlations
100 xp
Internal reliability
100 xp
When to use EFA
50 xp
2. 2

### Multidimensional EFA

This chapter will show you how to extend the single-factor EFA you learned in Chapter 1 to multidimensional data.

3. 3

### Confirmatory Factor Analysis

This chapter will cover conducting CFAs with the sem package. Both theory-driven and EFA-driven CFA structures will be covered.

4. 4

### Refining your measure and/or model

This chapter will reinforce the difference between EFAs and CFAs and offer suggestions for improving your model and/or measure.

### In the following Tracks

#### Statistician with R

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Datasets

Generic Conspiracist Beliefs Scale (GCBS) dataset

Collaborators

Jennifer Brussow

Psychometrician at Ascend Learning

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## Don’t just take our word for it

*4.1
from 12 reviews
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• S.Satheesh K.
5 months

Easy to Understand and follow code.

• Nicolas F.
6 months

This course goes over how to perform factor analysis which can be helpful for creating psychometric tests. I do not work on this field, but it was extremely helpful to see how the tests can be ran R.

• Dimitris L.
10 months

excellent course

• Edwin A.

A recommended course to learn about factor analysis in R.

• Lucas S.
7 months

It gives you a short introduction, but it falls short of the importance of using theory to build instruments and analyze psychometric properties.

"Easy to Understand and follow code."

S.Satheesh K.

"This course goes over how to perform factor analysis which can be helpful for creating psychometric tests. I do not work on this field, but it was extremely helpful to see how the tests can be ran R."

Nicolas F.

"excellent course"

Dimitris L.