
<WRAP centeralign>##Statistics Seminar##\\ Department of Mathematical Sciences</WRAP>

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^  **DATE:**|Thursday, March 11, 2021 |
^  **TIME:**|1:15pm -- 2:15pm |
^  **LOCATION:**|Zoom meeting |
^  **SPEAKER:**|Xinhai Zhang, Binghamton University |
^  **TITLE:**|A Simple Method for Estimating Interactions Between a Treatment and a Large Number of Covariates  |
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<WRAP centeralign>**Abstract**</WRAP>
In the paper 'A Simple Method for Estimating Interactions Between a
Treatment and a Large Number of Covariates’ by Lu TIAN, Ash A. ALIZADEH, Andrew J.
GENTLES, and Robert TIBSHIRANI, they propose a simple method for modeling
interactions between the treatment and covariates. The idea is to modify the
covariate in a simple way, and then ﬁt a standard model using the modiﬁed covariates
and no main effects. They show that coupled with an efﬁciency augmentation
procedure, this method produces clinically meaningful estimators in a variety of
settings. It can be useful for practicing personalized medicine: determining from a
large set of biomarkers, the subset of patients that can potentially beneﬁt from a
treatment.
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