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Exploratory Graph Analysis with R - Online Course

A 3-Day Livestream Seminar Taught by

Hudson Golino
Course Dates: Ask about upcoming dates
Schedule: All sessions are held live via Zoom. All times are ET (New York time).

10:00am-12:30pm ET (convert to your local time)
1:30pm-3:30pm ET

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A Network Psychometrics Approach to Structural Validity, Item Analysis, and Dimension Analysis

Researchers and applied professionals from many different fields, including psychology, sociology, education, political science, and the health sciences, have undoubtedly faced at least one of the following questions:

  • How many factors (latent dimensions) are being assessed by my instrument (test, questionnaire, survey, etc.)?
  • How stable is the dimensionality solution?
  • How good are my items? Do they replicate into the same latent dimensions or not?
  • How can I compare multiple dimensionality configurations (or solutions)?
  • Is my instrument structurally valid?
  • Are my items reliable, or do they merely seem reliable because we are using the common “cheating by repeating” approach?
  • How can I answer all these questions if I have (intensive) longitudinal data instead of cross-sectional data?

Too many important questions.

Or maybe you’re just interested in text mining and want to analyze data from social media in order to estimate latent variables.

Maybe you have heard a lot about network psychometrics and want to learn more about it.

Or, being more creative, you just want to know what Russian trolls have to do with dimensionality assessment and reduction and item analysis.

Again, exciting and important questions.

If these are questions you’ve asked yourself, and you’ve been scratching your head staring at the dataset on the screen in front of you, this course is what you’ve been looking for.

Starting March 16, we are offering this seminar as a 3-day synchronous*, livestream workshop held via the free video-conferencing software Zoom. Each day will consist of two lecture sessions which include hands-on exercises, separated by a 1-hour break. You are encouraged to join the lecture live, but will have the opportunity to view the recorded session later in the day if you are unable to attend at the scheduled time.

*We understand that finding time to participate in livestream courses can be difficult. If you prefer, you may take all or part of the course asynchronously. The video recordings will be made available within 24 hours of each session and will be accessible for four weeks after the seminar, meaning that you will get all of the class content and discussions even if you cannot participate synchronously. 

Closed captioning is available for all live and recorded sessions. Live captions can be translated to a variety of languages including Spanish, Korean, and Italian. For more information, click here.


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"...I was able to apply the theoretical concepts and practical applications directly to my own research questions."

“I would like to thank Hudson Golino for the interesting and very helpful course. I was able to learn a lot about the theoretical background of network analysis and the idea behind exploratory graph analysis. I especially liked being able to apply this acquired knowledge directly in the different R activities. Even though I was unfortunately not able to attend the course live, I was able to take a lot from the questions of the other participants as well as from Dr. Golino’s explanations when watching the recorded videos. The course had a high practical relevance for me, as I was able to apply the theoretical concepts and practical applications directly to my own research questions. Thank you very much for the great course!” 

Lena Rader

Institute of Medical Psychology

"Hudson’s course is well organized with excellent supporting materials..."

“This course provides a cogent and timely presentation on a topic that is critical to advancing network science and psychometrics. Hudson’s course is well organized with excellent supporting materials and exercises in R. The opportunity to use your own data is a great plus. I enjoyed learning about the connections between foundations of factor analysis and graph theory.” 

Larry Price

Texas State University

“I enjoyed the practical examples..."

“I enjoyed the practical examples and the instructor’s deep knowledge of, and passion for, EGA.” 

Avraam Papastathopoulos,

University of Sharjah