Please find information below on an upcoming webinar, sponsored by the Mental Health Statistics Section.
Title: Randomization Tests for Weak Null Hypotheses
Presenter: Dr. Peng Ding, University of California, Berkeley
Date and Time: Wednesday, April 21, 12:00 p.m. – 2:00 p.m. Eastern time
Sponsor: Mental Health Statistics Section
Registration Deadline: Tuesday, April 20, at 12:00 p.m. Eastern time
Description: The Fisher randomization test (FRT) is appropriate for any test statistic, under a sharp null hypothesis that can recover all missing potential outcomes. However, it is often sought after to test a weak null hypothesis that the treatment does not affect the units on average. To use the FRT for a weak null hypothesis, we must address two issues. First, we need to impute the missing potential outcomes although the weak null hypothesis cannot determine all of them. Second, we need to choose a proper test statistic. For a general weak null hypothesis, we propose an approach to imputing missing potential outcomes under a compatible sharp null hypothesis. Building on this imputation scheme, we advocate a studentized statistic. The resulting FRT has multiple desirable features. First, it is model-free. Second, it is finite-sample exact under the sharp null hypothesis that we use to impute the potential outcomes. Third, it conservatively controls large-sample type I error under the weak null hypothesis of interest. Therefore, our FRT is agnostic to the treatment effect heterogeneity. We establish a unified theory for general factorial experiments and extend it to stratified and clustered experiments. We also propose a general strategy for covariate-adjusted FRTs.
Presenter: Dr. Peng Ding is an assistant professor in the Department of Statistics at the University of California, Berkeley. His research interests are causal inference in experimental and observational studies, missing data, measurement error, and selection bias.
Registration:
ASA Members: $20
Student ASA Member: $15
Nonmembers: $35
Each registration is allowed one connection to the webinar. Multiple persons are encouraged to view each registered connection (for example, by projecting the webinar in a conference room).
Registration Link: https://www.amstat.org/ASA/Education/Web-Based-Lectures.aspx#RTWNH
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Adam Ciarleglio
Assistant Professor
George Washington University
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