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| Duration: | 1 hour |
|---|---|
| Where: | Join us from anywhere! |
| Cost: | Free—but registrations are limited |
This talk introduces the basic concepts of causal inference, including counterfactuals and potential outcomes. I will demonstrate how to use Stata's teffects suite of commands to fit causal models using propensity-score matching, inverse-probability weighting, regression adjustment, "doubly robust" estimators that use a combination of inverse-probability weighting with regression adjustment, and nearest-neighbor matching.
The webinar is free, but you must register to attend. Registrations are limited so register soon.
We will send you an email prior to the start with instructions on how to access the webinar.
Chuck Huber is Director of Statistical Outreach at StataCorp LLC and Adjunct Associate Professor of Biostatistics at the Texas A&M School of Public Health and at the New York University School of Global Public Health. In addition to working with Stata's team of software developers, he produces instructional videos for the Stata YouTube channel, writes blog entries, develops online NetCourses, and gives talks about Stata at conferences and universities. Most of his current work is focused on statistical methods used by behavioral and health scientists. He has published in the areas of neurology, human and animal genetics, alcohol and drug abuse prevention, nutrition, and birth defects. Dr. Huber currently teaches survey sampling at NYU and introductory biostatistics at Texas A&M, where he previously taught categorical data analysis, survey data analysis, and statistical genetics.
