Estimating Average Treatment Effects with R

Ryerson Urban Analytics Institute is pleased to invite you to a webinar on:

Causal Inference by Empirical Balancing Calibration Weighting

When: November 23, 2020. 1:30 PM (EST)

To Register, please visit


The webinar introduces ATE, an R package for estimating the average treatment effects using calibration estimators. The webinar presents the theory of calibration estimators in the context of estimating the average treatment effect, including the treatment effect on the treated, treatment effect for multiple treatment arms and their corresponding variances.
The webinar also presents a hands-on tutorial demonstrating the ATE package. The tutorial will demonstrate how to install the ATE package, import and process data, and estimate the average treatment effects. Participants are encouraged to follow the tutorial using R (available at A web-based instance of R can be also be used (

Presenter: Asad Haris, Ph.D.
Post Doctoral Fellow
Dept. of Epidemiology, Biostatistics & Occupational Health
McGill University