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Constructing Balanced Treatment and Control Groups for Observational Study Data Using Random Forest

With Juanjuan Fan, Professor, Department of Mathematics and Statistics, San Diego State University. In order to derive unbiased inference from observational data, matching methods are often applied to produce balanced treatment and control groups in terms of all background variables.  Fan's proposed random forest based matching methods are applied to data from the National Health and Nutrition Examination Survey (NHANES). Her results show that the proposed methods can produce well balanced treatment and control groups.

Thursday, January 11 at 4:00pm to 5:00pm

Donald Bren Hall, 6011
6210 Donald Bren Hall, Irvine, CA 92697

Event Type

Lectures / Presentations


Faculty, General Public, Students, Graduate Students





Information & Computer Sciences



Event Sponsor

Department of Statistics

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