Matching and Weighting for Causal Inference with R June 2019

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A 2-Day Seminar Taught by Stephen Vaisey, Ph.D.

This course offers an in-depth introduction to matching and weighting methods using the R package. 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.

Researchers use matching and weighting to identify the causal effect of a treatment on an outcome — such as the effect of a college education on earnings, the effect of divorce on child outcomes, or the effect of a training program on employee productivity — when assignment to the treatment is not random. A major advantage of these techniques over standard regression methods is that they can easily produce different 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.

This seminar will guide participants from simple exact matching to recent developments like coarsened exact matching, entropy balancing, and matching frontier techniques that show how effects vary across the full range of possible match quality. We will also show how to integrate matching with regression to create “doubly robust” estimates of causal effects. Participants will get practical experience by working through exercises from the social and health sciences.

Though the seminar will focus on hands-on understanding, we will also use causal graphs (directed acyclic graphs or DAGs) to look more deeply into the assumptions required to achieve unbiased estimates. Participants will learn how these graphs can be used in their own research.

This is a hands-on course with at least one hour each day devoted to carefully structured and supervised assignments.

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Venue Phone: 312-573-0800

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Address:
165 E Ontario Street, Chicago, Illinois, 60611, United States