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Factor Analysis in R

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

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4 Hours13 Videos45 Exercises
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Course Description

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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In the following Tracks

Statistician with R

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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.

    Play Chapter Now
    Introduction to Exploratory Factor Analysis (EFA)
    50 xp
    Starting out with a unidimensional EFA
    100 xp
    Viewing and visualizing the factor loadings
    100 xp
    Interpreting individuals' factor scores
    100 xp
    Overview of the measure development process
    50 xp
    Descriptive statistics of your dataset
    100 xp
    Splitting your dataset
    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
For Business

GroupTraining 2 or more people?

Get your team access to the full DataCamp library, with centralized reporting, assignments, projects and more

In the following Tracks

Statistician with R

Go To Track

Datasets

Generic Conspiracist Beliefs Scale (GCBS) dataset

Collaborators

Collaborator's avatar
Chester Ismay
Collaborator's avatar
Becca Robins
Jennifer Brussow HeadshotJennifer 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.
    6 months

    Easy to Understand and follow code.

  • Nicolas F.
    7 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.
    11 months

    excellent course

  • Edwin A.
    over 1 year

    A recommended course to learn about factor analysis in R.

  • Lucas S.
    8 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.

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