st (version 1.2.7)

studentt.stat: (Paired) Student t Statistic

Description

These functions provide a simple interface to compute (paired) Student t statistics in the analysis of high-dimensional case-control studies.

Usage

studentt.stat(X, L, var.equal=TRUE, paired=FALSE)
studentt.fun(L, var.equal=TRUE)

Arguments

X

data matrix. Note that the columns correspond to variables (``genes'') and the rows to samples.

L

factor with class labels for the two groups. If only a single label is given then a one-sample t score against 0 is computed.

var.equal

assume equal (default) or unequal variances in each group.

paired

compute paired t-score (default is to use unpaired t-score).

Value

The studentt.stat function returns a vector containing the t-statistic for each variable. It can be specified whether the variances in the two groups are equal. A paired t-score can also be computed.

The studentt.fun function returns a function that computes the t-score statistics when applied to a data matrix (useful for simulations).

See Also

shrinkt.stat, shrinkcat.stat.

Examples

# NOT RUN {
# load st library 
library("st")

# load Choe et al. (2005) data
data(choedata)
X <- choe2.mat
dim(X) # 6 11475  
L <- choe2.L
L

# L may also contain some real labels
L = c("group 1", "group 1", "group 1", "group 2", "group 2", "group 2")

# student t statistic (equal variances)
score = studentt.stat(X, L)
order(score^2, decreasing=TRUE)[1:10]
# [1] 11068   724  9990 11387 11310  9985  9996 11046    43    50

# the same computed with standard R methods (slower!)
#score2 = apply(X, 2, function(x) t.test(x ~ L, var.equal=TRUE)$statistic)
#sum((score-score2)^2)

# student t statistic (unequal variances)
score = studentt.stat(X, L, var.equal=FALSE)
order(score^2, decreasing=TRUE)[1:10]
# [1] 11068   724  9990 11387 11310  9985  9996 11046    43    50

# the same computed with standard R methods (slower!)
#score2 = apply(X, 2, function(x) t.test(x ~ L, var.equal=FALSE)$statistic)
#sum((score-score2)^2)

# paired student t statistic
score = studentt.stat(X, L, paired=TRUE)
order(score^2, decreasing=TRUE)[1:10]
# [1] 9985  7239  5393 11387 11310  9942 10238  9996 11015 11276

# the same computed with standard R methods (slower!)
#score2 = apply(X, 2, function(x) t.test(x ~ L, paired=TRUE)$statistic)
#sum((score-score2)^2)
# }