[BioC] more multtest problems
michael watson (IAH-C)
michael.watson at bbsrc.ac.uk
Thu Mar 11 17:17:07 MET 2004
Hi
Even after some very good help, I am still confused by multtest.
Below is the output from my analysis. What I basically do is read in some data, use t.test() to perform a two-tailed, unequal variance t-test on the first row, then use mt.maxT() to perform a t-test on all the rows and then compare the results.
What I have found is that although t.test() and mt.maxT() produce the same t value (0.9796), the raw p-values differ (0.3954 vs 0.54285714).
Why is rawp from mt.maxT different to the p-value from t.test()
Thanks!
Mick
> library(multtest)
> data <- read.table("average.txt", header=TRUE, sep="\t", quote="\"")
> cl = c(1,1,1,1,0,0,0)
> # do two-tailed t-test, unequal variance
> t <- t.test(data[1,1:4],data[1,5:7], alternative="two.sided", var.equal=FALSE)
> t
Welch Two Sample t-test
data: data[1, 1:4] and data[1, 5:7]
t = 0.9796, df = 3.199, p-value = 0.3954
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-2.407296 4.659662
sample estimates:
mean of x mean of y
1.130890500 0.004707667
> multt <- mt.maxT(data,cl,test="t",side="abs")
We'll do complete enumerations
We're doing 35 complete permutations
b=1 b=2 b=3 b=4 b=5 b=6 b=7 b=8 b=9 b=10
b=11 b=12 b=13 b=14 b=15 b=16 b=17 b=18 b=19 b=20
b=21 b=22 b=23 b=24 b=25 b=26 b=27 b=28 b=29 b=30
b=31 b=32 b=33 b=34 b=35 >
> multt
index teststat rawp adjp
1 4 2.4344730 0.02857143 0.02857143
2 3 1.7019798 0.25714286 0.25714286
3 5 1.5719193 0.08571429 0.25714286
4 6 1.3674557 0.02857143 0.25714286
5 2 1.1519341 0.20000000 0.28571429
6 1 0.9796023 0.54285714 0.54285714
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