Estimating the Local False Discovery Rate via a Bootstrap Solution to the Reference Class Problem: Application to Genetic Association Data

Estimating the Local False Discovery Rate via a Bootstrap Solution to the Reference Class Problem: Application to Genetic Association Data

Modern scientific technology such as microarrays, imaging devices, genome-wide association studies or social science surveys provide statisticians with hundreds or even thousands of tests to consider simultaneously. Testing many thousands of null hypotheses may increase the number of Type $I$ errors...

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Bibliographic Details
Main Author: Abbas Aghababazadeh, Farnoosh
Other Authors: Bickel, David
Language:en
Published: Université d'Ottawa / University of Ottawa 2015
Subjects:
Multiple Testing
Local False Discovery Rtae
Reference Class
Bias-variance Trade Off
Tuning Parameter
Bootstrap Approach
Online Access:http://hdl.handle.net/10393/33367
http://dx.doi.org/10.20381/ruor-3974

Internet

http://hdl.handle.net/10393/33367
http://dx.doi.org/10.20381/ruor-3974

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