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Matching and Weighting for Causal Inference with R - Online Course

A 4-Day Livestream Seminar Taught by

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

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

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This course offers an in-depth introduction to matching and weighting methods using R. Matching and weighting are quasi-experimental techniques for estimating causal effects from observational data using the potential outcomes or counterfactual framework. They are often (but not always) based on propensity scores. These techniques are now widely used in the social sciences, health sciences, management, and public policy.

Starting July 25, we are offering this seminar as a 4-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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Computing

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“The instructor was FANTASTIC!"

“The instructor was FANTASTIC! Dr. Vaisey’s enthusiasm and humor is what made this course so much fun. His ability to clearly explain difficult concepts, such as counterfactuals, were critical to everything else in the course making sense. The examples he used were always very clear. I liked the progression of how the course built upon itself in a very intentional format. Dr. Vaisey presented information on techniques that he recommended against using, and explained why it was relevant to understand these concepts as a pre-requisite for the next topic. He was incredibly responsive to questions, both during the live sessions and on the Slack message board.” 

James Smoliga

High Point University

"I found the course approach very useful and practical as it showed how to handle complex real-world data as well as simpler examples.”

“This was a great course. I had fun learning new things. Dr. Vaisey is a great teacher, and I am not surprised that I am finding myself taking his courses again. I found the course approach very useful and practical as it showed how to handle complex real-world data as well as simpler examples.”

Tahereh Dehdarirad

Chalmers University of Technology

"It was just the right level of material, not too basic nor too advanced."

“I liked several points about this seminar: that Steve was not a statistician by training, so he had a very approachable way of covering the material; it was just the right level of material, not too basic nor too advanced; the range of techniques that were covered; how fun it was.”

Joana Cruz

University College of London

"I came away with an understanding of the core principles..."

“Steve introduced us to best practices in weighting and matching while making causal inferences. I appreciated his research expertise and practical insight when applying these techniques. I came away with an understanding of the core principles behind these approaches. I highly recommend this course for social science researchers who wish to make causal inferences with observational data.”

Bill Burns

California State University San Marcos

“I liked the mix of lectures with exercises.”

“I liked the mix of lectures with exercises. Stephen’s teaching was also very nice with lots of examples and analogies.”

Andre Bedendo de Souza

University of York

“This course offered a good combination of theory/practice/R code."

“This course offered a good combination of theory/practice/R code. I also appreciated the ability to ask questions.”

Beth Chance

California Polytechnic State University

"The simple examples to illustrate different treatment effects was helpful as well."

“I liked seeing the practical applications in the examples during the course work. The simple examples to illustrate different treatment effects was helpful as well.”

Johanna van Zyl

Baylor Scott & White Research Institute