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- Multiple Testing Procedures for Controlling Tail Probability Error Rates
-
- Sandrine Dudoit, Division of Biostatistics, School of Public Health, University of California, Berkeley
- Mark J. van der Laan, Division of Biostatistics, School of Public Health, University of California, Berkeley
- Merrill D. Birkner, Division of Biostatistics, School of Public Health, University of California, Berkeley
-
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- Abstract:
- The present article discusses and compares multiple testing procedures
(MTP) for controlling Type I error rates defined as tail probabilities for
the number (gFWER) and proportion (TPPFP) of false positives among the
rejected hypotheses.
Specifically, we consider the gFWER- and TPPFP-controlling MTPs proposed
recently by Lehmann & Romano (2004) and in a series of four articles by
Dudoit et al. (2004), van der Laan et al. (2004b,a), and Pollard & van der
Laan (2004).
The former Lehmann & Romano (2004) procedures are marginal, in the sense
that they are based solely on the marginal distributions of the test
statistics, i.e., on cut-off rules for the corresponding unadjusted
p-values.
In contrast, the procedures discussed in our previous articles take into
account the joint distribution of the test statistics and apply to general
data generating distributions, i.e., dependence structures among test
statistics.
The gFWER-controlling common-cut-off and common-quantile procedures of
Dudoit et al. (2004) and Pollard & van der Laan (2004) are based on the
distributions of maxima of test statistics and minima of unadjusted
p-values, respectively.
For a suitably chosen initial FWER-controlling procedure, the gFWER- and
TPPFP-controlling augmentation multiple testing procedures (AMTP) of van
der Laan et al. (2004a) can also take into account the joint distribution
of the test statistics.
Given a gFWER-controlling procedure, we also propose AMTPs for controlling
tail probability error rates, Pr(g(V_n,R_n) > q), for arbitrary functions
g(V_n,R_n) of the numbers of false positives V_n and rejected hypotheses
R_n.
The different gFWER- and TPPFP-controlling procedures are compared in a
simulation study, where the tests concern the components of the mean
vector of a multivariate Gaussian data generating distribution.
Among notable findings are the substantial power gains achieved by joint
procedures compared to marginal procedures.
- Subject Area:
- Statistical Theory and Methods
- Suggested Citation:
- Sandrine Dudoit, Mark J. van der Laan, and Merrill D. Birkner,
"Multiple Testing Procedures for Controlling Tail Probability Error Rates"
(December 2004).
U.C. Berkeley Division of Biostatistics Working Paper Series.
Working Paper 166.
http://www.bepress.com/ucbbiostat/paper166