Causal Inference in R Using MatchIt and WeightIt with Noah Greifer

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About this Seminar

MatchIt and WeightIt are powerful R packages that simplify the implementation of matching and weighting methods for causal inference, offering a consistent, user-friendly interface. They enable researchers to transparently balance covariates and estimate treatment effects using traditional and modern approaches—all within a flexible and reproducible workflow.

This seminar will introduce matching and weighting methods utilizing MatchIt and WeightIt for estimating causal effects in observational studies. We will balance conceptual foundations—like the potential outcomes framework and distinctions between average treatment effects (ATEs) and average treatment effects on the treated (ATTs)—with hands-on practice. We'll also cover important related topics like interpreting results, data visualization, and communicating trade-offs.

By the end of this course, you will be able to:

-Implement matching and weighting methods in R using the MatchIt and WeightIt packages.
-Evaluate and interpret the performance of matching and weighting methods.
-Estimate treatment effects and validly compute measures of uncertainty.
-Communicate results clearly with visualizations and interpretations of trade-offs.

This seminar will use R for all computing tasks.