May 24 SFASA Seminar
A Simple
Method for Detecting Interactions Between a Treatment and a Large Number of
Covariates
Speaker: Lu Tian , Assistant Professor, Health Research & Policy -
Biostatistics
Date: Thursday,
May 24th
Time: 4:30
P.M. - 6:30 P.M.
Location: Stanford
University, Center for Clinical Sciences Research (CCSR), Room 4105
Abstract:
Co-authors: Lu
Tian, Ash Alizadeh, Andrew
Gentles and Robert Tibshirani
We consider a setting in
which we have a treatment and a large number of covariates for a set of
observations, and wish to model their relationship with an outcome of interest.
We 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. We show that
coupled with an efficiency augmentation procedure, this method produces valid
inferences in a variety of settings. It can be useful for personalized
medicine: determining from a large set of biomarkers the subset of patients
that can potentially benefit from a treatment. We apply the method to both
simulated datasets and gene expression studies of cancer. The modified data can
be used for other purposes, for example large scale
hypothesis testing for determining which of a set of covariates interact with a
treatment variable.
The
map can be found from the following website: med.stanford.edu/maps/medical_buildings.html
Direction
to Campus and medical school can be found from the following link: med.stanford.edu/maps/to-sumc.html
Use
of the public transportation (Cal Train) is highly recommended. Parking is free
after 4pm.
Return
to Bay Area ASA
Homepage