Package: multtest
Title: Resampling-based multiple hypothesis testing
Version: 2.8.0
Author: Katherine S. Pollard, Houston N. Gilbert, Yongchao Ge, Sandra
Taylor, Sandrine Dudoit
Description: Non-parametric bootstrap and permutation resampling-based
multiple testing procedures (including empirical Bayes methods)
for controlling the family-wise error rate (FWER), generalized
family-wise error rate (gFWER), tail probability of the
proportion of false positives (TPPFP), and false discovery rate
(FDR).  Several choices of bootstrap-based null distribution
are implemented (centered, centered and scaled,
quantile-transformed). Single-step and step-wise methods are
available. Tests based on a variety of t- and F-statistics
(including t-statistics based on regression parameters from
linear and survival models as well as those based on
correlation parameters) are included.  When probing hypotheses
with t-statistics, users may also select a potentially faster
null distribution which is multivariate normal with mean zero
and variance covariance matrix derived from the vector
influence function.  Results are reported in terms of adjusted
p-values, confidence regions and test statistic cutoffs. The
procedures are directly applicable to identifying
differentially expressed genes in DNA microarray experiments.
Maintainer: Katherine S. Pollard <kpollard@gladstone.ucsf.edu>
Depends: R (>= 2.9.0), methods, Biobase
Imports: survival, MASS
Suggests: snow
License: LGPL
biocViews: Microarray, DifferentialExpression, MultipleComparisons
LazyLoad: yes
Packaged: 2011-04-14 06:11:16 UTC; biocbuild
Repository: CRAN
Date/Publication: 2011-04-26 19:18:14

Title: Common Multiple Testing Procedures and Gatekeeping Procedures
Author: Alex Dmitrienko, Eric Nantz, and Gautier Paux, with
Description: Implementation of commonly used p-value-based and
parametric multiple testing procedures (computation of adjusted
p-values and simultaneous confidence intervals) and parallel
gatekeeping procedures based on the methodology presented in
the book "Multiple Testing Problems in Pharmaceutical
Statistics" (edited by Alex Dmitrienko, Ajit C. Tamhane and
Frank Bretz) published by Chapman and Hall/CRC Press 2009.
Depends: R (>= 2.1.0), stats, mvtnorm (>= 0.9)