American Statistical Association
New York City
Metropolitan Area Chapter

Mailman School of Public Health
Columbia University
Department of Biostatistics Colloquium



SIMULTANEOUS INFERENCE:
WHEN SHOULD HYPOTHESIS TESTING PROBLEMS BE COMBINED?

by

Brad Efron
Stanford University


Abstract

Statisticians these days are often presented with hundreds or thousands of hypothesis testing problems to evaluate at the same time, generated from modern scientific technologies such as microarrays, fMRI devices, satellite imagers, and flow cytometry machines. The relevant statistical literature tends to begin with the tacit assumption that a single combined analysis, for instance a False Discovery Rate assessment, should be applied to the entire set of problems at hand. I will give examples to show the dangers of this assumption. A little bit of theory on when to separate and when to combine will be presented, but the examples make clear that actual situations can be dauntingly difficult to decide.


Date: Thursday, April 5, 2007
Time: 4:00 - 5:00 P.M.
Location: Columbia Presbyterian Medical Center
Vanderbilt Clinic
Humphreys Auditorium - 14th Floor, Room 240
622 West 168th Street
(between Broadway and Fort Washington Avenue)
New York, New York

RESERVATIONS ARE NOT REQUIRED

Refreshments will be served at 3:30 P.M. in the
Biostatistics Conference Room (Room 627).


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