The function FDR performs different multiple test procedures for
controlling the false discovery rate (FDR).
function [O] = fdr(Input,n1,samp) returns the number of rejected hypotheses,
the rank (O(:,1)), the indices of the rejected hypotheses (O(:,2)), the adjusted p-values
(O(:,3)) and the unadjusted p-values (O(:,4)) for the procedure of Benjamini
and Yekutieli (1995) with the significance level alpha=0.05.
----------
INPUT
These input arguments are required:
Input: data matrix with the size [n,k]
n1: number of patients in group one (0 < n1 <= n ),
restricted by the kind of samp
samp: kind of sample
single sample 'single' (n1 = n)
paired sample 'paired' (n1 = n/2; n must be even)
independent sample 'indept' (n1 < n)
-----
[...] = fdr(...,'PARAM1',VAL1,'PARAM2',VAL2,...) specifies additional
parameters and their values. Valid parameters are the following:
Parameter Value
'test' Value for single sample
'ttest' to compute the t-Test
assumption : normal(gaussian) distribution
'wilcox' to compute the Wilcoxen signed rank test
assumption : symmetrical distribution
'sign' (the default) to compute the sign-test
assumption : none
Value for paired sample
'ttest' to compute the t-Test
assumption : normal(gaussian) distribution
'wilcox' to compute the Wilcoxen signed rank test
assumption : symmetrical distribution
'sign' (the default) to compute the sign-test
assumption : none
Value for independent sample
'ttest' to compute the t-Test
assumption : normal(gaussian) distribution
'wilcox' (the default) to compute the Wilcoxen rank test (Wilcoxen-Man-Whitney-Test)
assumption : none
'tail' The alternative hypothesis against which to compute
p-values for testing the hypothesis of no differences.
Choices are:
tail Alternative Hypothesis
'~=' (the default) "there is a significant difference" (two-sided test)
'>' "the values of group 1 are higher than the values of group 2" (one-sided test)
'<' "the values of group 1 are smaller than the values of group 2" (one-sided test)
---
'proc' 'BH' (the default) chooses the procedure of Benjamini and Hochberg (1995)
'BL' chooses the procedure of Benjamini and Liu (2001)
'BKY' chooses the procedure of Benjamini, Krieger and Yekutieli (2001)
---
'alpha' 0.05 (the default) significance level
for a other value: 0<alpha<=0.2
-----------
OUTPUT
[O] = fdr(Input,n1,samp) returns the rank (O(:,1)),
the indices of the rejected hypotheses (O(:,2)),
the adjusted p-values (O(:,3)) and the unadjusted p-values (O(:,4)).
-----------
REFERENCES:
[1] Hemmelmann C, Horn M, Suesse T, Vollandt R, Weiss S.
New concepts of multiple tests and their use for evaluating high-dimensional EEG data.
J Neurosci Methods. 2005 Mar 30;142(2):209-17.
[2] Hemmelmann C, Horn M, Reiterer S, Schack B, Suesse T, Weiss S.
Multivariate tests for the evaluation of high-dimensional EEG data.
J Neurosci Methods. 2004 Oct 15;139(1):111-20.
Copyright (C) 2006,2007 Claudia Hemmelmann <claudia.hemmelmann@mti.uni-jena.de>
Adapted by A Schloegl <a.schloegl@ieee.org> 2006,2007
***
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Library General Public
License as published by the Free Software Foundation; either
Version 2 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Library General Public License for more details.
You should have received a copy of the GNU Library General Public
License along with this library; if not, write to the
Free Software Foundation, Inc., 59 Temple Place - Suite 330,
Boston, MA 02111-1307, USA.
--------------------------------------------------------------------------