Harvard Catalyst, January 18, 2018, Boston, MA
Channel Network Conference of the International Biometric Society, April 24, 2017, Hasselt, Belgium
Sherri Rose taught a half-day short course on targeted learning methods at the Channel Network Conference of the International Biometric Society (IBS). This conference is organized by the Belgium, France, Great Britain/Ireland, and Netherlands regions of the IBS. Download the slides; code is posted on GitHub.
CIMPOD Conference, February 27-28, 2017, Bethesda, MD
Sherri Rose taught two half-day short courses on targeted learning at the Causal Inference Methods for Patient Centered Outcomes Research using Observational Data (CIMPOD) Conference. Download the slides from Day 1 and Day 2.
Columbia Causal Inference Conference, November 10, 2016, New York, NY
MDEpiNet Annual Meeting, September 30, 2015, Silver Spring, MD
Atlantic Causal Inference Conference, May 19, 2015, Philadelphia, PA
University of Utah, April 23-24, 2014, Salt Lake City, UT
A seminar on machine learning for prediction in epidemiology and a half-day short course on targeted learning were presented at the University of Utah by professor Sherri Rose. Download slides: seminar, short course.
Joint Statistical Meetings, July 29, 2012, San Diego, CA
A one-day continuing education course, Targeted Learning: Causal Inference for Observational and Experimental Data, was presented at the 2012 Joint Statistical Meetings. The instructors were Mark van der Laan, Maya Petersen, and Sherri Rose, and the course summary is available online. Slide decks from the course can be downloaded as a zip file.
Forum for Collaborative HIV Research, September 26-28, 2011, Washington, DC
The Forum for Collaborative HIV Research and the University of California, Berkeley School of Public Health presented the short course Statistical Methods for Causal Inference in Observational and Randomized Studies with instructors Mark van der Laan, Maya Petersen, and Sherri Rose. Course materials, including outline, slides, and sample code can be found online.