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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. Researchers use matching and weighting to identify the causal effect of a treatment on an outcome — such as the effect of smoking on health or the effect of divorce on child outcomes — when assignment to the treatment is not random. Many of these techniques rely on traditional propensity scores but the course will also cover newer techniques that are not propensity-score based.

Matching and weighting have two notable advantages over standard regression methods. First, they are less dependent on correct model specification. Second, they can easily produce separate estimates of causal effects for subjects who are likely to receive the treatment and for those who are unlikely to receive it, a distinction that is especially important for policy work.

Starting June 18, 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. 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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“Dr. Vaisey made very challenging concepts easy to consume."

“Dr. Vaisey was a fantastic instructor. He made very challenging concepts easy to consume, and was responsive to all questions. I loved the examples as well.”

William Hall

University of Ottawa

"Stephen is very enthusiastic and somehow managed to make statistics interesting.”

“I appreciated how Dr. Vaisey offered clear explanations, not just the ‘how’, but explaining the ‘why’. Stephen is very enthusiastic and somehow managed to make statistics interesting.”

Michelle Orme

ICERA Consulting Ltd.

“I liked the way simple explanations were given for complicated concepts..."

“I liked the way simple explanations were given for complicated concepts, making it easy to understand and also retain that understanding.”

Mubarika (Rika) Alavi

Kaiser Permanente

"I was cracking up all the time.”

“I am very thankful for the code that I can replicate on my own time. I loved having access to the resources that the instructor was using. The instructor responded to all questions! I loved his sense of humor –thank goodness my mic was closed; I was cracking up all the time.”

Sara Avila

University of Colorado, Boulder

“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