Fall Seminar Series - November 17, 2005
University of Minnesota
School of Statistics
College of Liberal Arts
Some
Recent Work on Multiple Comparisons: Non-discovery Rate and Stratified
False Discovery Control
Radu Craiu
Department of Statistics
University of Toronto
Thursday, November 17, 2005
3:30 PM, 115
Ford Hall
Minneapolis, East Bank Campus
Social at 3:00 PM, 300 Ford Hall
Abstract
The
multiplicity problem has become increasingly important in many
scientific studies. The control of false discovery rate (FDR)
represents a different point of view than the classical control of
the familywise error rate (FWER). In this talk, I will present our
recent work on two FDR-related problems. I will first discuss a new
quantity of interest, non-discovery rate (NDR) which is the fraction of
non-rejections among the cases in which the null hypotheses are
false. I will describe the property and utility of NDR and use it to
address several issues including a). type II error rate and power in
the context of multiple hypothesis testing. b). trade-off relationship
between FDR and NDR. c). choice of an appropriate FDR level. Secondly,
I will investigate the performance of false discovery control after a
set of p-values has been stratified based on auxilliary information.
Under the fixed rejection region
framework, I will demonstrate that the aggregated FDR is a weighted
average of
the stratified FDR. Under the fixed FDR framework, I will provide the
condition under which the expected total number of correct
rejections from the stratified FDR approach is greater than that from
the aggregated FDR approach. For both problems, I will illustrate the
ideas with analyses of microarray gene-expression data, pedigree
data and genome-wide association data.
This is joint work with Lei Sun from the Departments of Public Health
Sciences and Statistics, University of Toronto.