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Network Psychometrics with Exploratory Graph Analysis - Online Course

A 3-Day Livestream Seminar Taught by

Hudson Golino
Course Dates:

Wednesday, April 30 –
Friday, May 2, 2025

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

Watch Sample Video

An Innovative 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.

Bonus feature: All seminar participants will get exclusive access to the new EGA Wizard AI Assistant (requires a ChatGPT Plus subscription).

Starting April 30, 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. Captions can be translated to a variety of languages including Spanish, Korean, and Italian. For more information, click here.

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"This really turbocharged the way participants could apply these techniques to their own data."

“The careful, well sequenced pathway and the application to a series of useful examples that illustrated the workflow was great. This really turbocharged the way participants could apply these techniques to their own data. A couple of other participants and I were applying them in between sessions during the course.”

Stefano Occhipinti

The Hong Kong Polytechnic University

“Dr. Golino’s insightful teachings...ignited a passion within me for exploring the intricate connections in psychological networks further.”

“Dr. Golino’s insightful teachings have not only deepened my understanding of the subject but have also ignited a passion within me for exploring the intricate connections in psychological networks further.”

Chun Feng

The First Rehabilitation Hospital of Shanghai

“I really liked the combination of cutting-edge research...and personalized project assistance that this course had to offer.”

“I really liked the combination of cutting-edge research, expert insights, practical R code examples, effective interaction, and personalized project assistance that this course had to offer.”

Fai Cheong

Emory University

"I’m going to use this a great deal in the future.”

“I liked the various episodes and R code “breaks”. Hudson was an excellent instructor, and I was able to apply the EGA technique to a real project before the end of the second day. I’m going to use this a great deal in the future.”

John Tripp

Clemson University

"I cannot recommend the course highly enough.”

“This is truly a tremendous course. Professor Hudson Golino is an excellent teacher! He is very knowledgeable, supportive, and not only gives his time patiently, but provides the very latest updates. The hands-on exercises were superb. I cannot recommend the course highly enough.”

Anthony James

University of Oxford

“Hudson's didactic is amazing for such dense material.”

“Hudson’s didactic is amazing for such dense material. The tutorials in the hands-on activity are easy to follow and understand.”

Luiz Gustavo de Almeida

Institute Question of Science

"...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