mt.sample.teststat {multtest}  R Documentation 
Permutation distribution of test statistics and raw (unadjusted) pvalues
Description
These functions provide tools to investigate the permutation distribution
of test statistics, raw (unadjusted) pvalues, and class labels.
Usage
mt.sample.teststat(V,classlabel,test="t",fixed.seed.sampling="y",B=10000,na=.mt.naNUM,nonpara="n")
mt.sample.rawp(V,classlabel,test="t",side="abs",fixed.seed.sampling="y",B=10000,na=.mt.naNUM,nonpara="n")
mt.sample.label(classlabel,test="t",fixed.seed.sampling="y",B=10000)
Arguments
V 
A numeric vector containing the data for one of the variables (genes).

classlabel 
A vector of integers corresponding to observation (column)
class labels. For k classes, the labels must be integers
between 0 and k1. For the blockf test option,
observations may be divided into
n/k blocks of k observations each. The observations are
ordered by block, and within each block, they are labeled using the
integers 0 to k1.

test 
A character string specifying the statistic to be
used to test the null hypothesis of no association between the
variables and the class labels.
If test="t" , the tests are based on twosample Welch tstatistics
(unequal variances).
If test="t.equalvar" , the tests are based on twosample
tstatistics with equal variance for the two samples. The
square of the tstatistic is equal to an Fstatistic for k=2.
If test="wilcoxon" , the tests are based on standardized rank sum Wilcoxon statistics.
If test="f" , the tests are based on Fstatistics.
If test="pairt" , the tests are based on paired tstatistics. The
square of the paired tstatistic is equal to a block Fstatistic for k=2.
If test="blockf" , the tests are based on Fstatistics which
adjust for block differences
(cf. twoway analysis of variance).

side 
A character string specifying the type of rejection region.
If side="abs" , twotailed tests, the null hypothesis is rejected for large absolute values of the test statistic.
If side="upper" , onetailed tests, the null hypothesis is rejected for large values of the test statistic.
If side="lower" , onetailed tests, the null hypothesis is rejected for small values of the test statistic.

fixed.seed.sampling 
If fixed.seed.sampling="y" , a
fixed seed sampling procedure is used, which may double the
computing time, but will not use extra memory to store the
permutations. If fixed.seed.sampling="n" , permutations will
be stored in memory. For the blockf test, the option n was not implemented as it requires too much memory.

B 
The number of permutations. For a complete
enumeration, B should be 0 (zero) or any number not less than
the total number of permutations.

na 
Code for missing values (the default is .mt.naNUM=93074815.62 ).
Entries with missing values will be ignored in the computation,
i.e., test statistics will be based on a smaller sample size. This
feature has not yet fully implemented.

nonpara 
If nonpara ="y", nonparametric test statistics are computed based on ranked data.
If nonpara ="n", the original data are used.

Value
For mt.sample.teststat
, a vector containing B
permutation test statistics.
For mt.sample.rawp
, a vector containing B
permutation unadjusted pvalues.
For mt.sample.label
, a matrix containing B
sets of permuted class labels. Each row corresponds to one permutation.
Author(s)
Yongchao Ge, yongchao.ge@mssm.edu,
Sandrine Dudoit, http://www.stat.berkeley.edu/~sandrine.
See Also
mt.maxT
, mt.minP
, golub
.
Examples
# Gene expression data from Golub et al. (1999)
data(golub)
mt.sample.label(golub.cl,B=10)
permt<mt.sample.teststat(golub[1,],golub.cl,B=1000)
qqnorm(permt)
qqline(permt)
permt<mt.sample.teststat(golub[50,],golub.cl,B=1000)
qqnorm(permt)
qqline(permt)
permp<mt.sample.rawp(golub[1,],golub.cl,B=1000)
hist(permp)
[Package
multtest version 2.34.0
Index]