Hi,
If I set the p.adjust="none", does it meant that the output p values from the
pairwise.t.test will be the same as those from individual t.tests (set
var.equal=T, alternative="t")?
I actually got different p values from the two tests. See below. Is it supposed
to be this way?
Thanks
Johnny
> x
[1] 61.6 52.7 61.3 65.2 62.8 63.7 64.8 58.7 44.9 57.0 64.3 55.1 50.0 41.0
[15] 43.0 45.9 52.2 45.5 46.9 31.6 40.6 44.8 39.4 31.0 37.5 32.6 23.2 34.6
[29] 38.3 38.1 19.5 21.2 15.8 33.3 28.6 25.8
> Grp
[1] Yng Yng Yng Yng Yng Yng Yng Yng Yng Yng Yng Yng Med Med Med Med Med Med
[19] Med Med Med Med Med Med Old Old Old Old Old Old Old Old Old Old Old Old
Levels: Yng Med Old
> pairwise.t.test(x=x,g=Grp,p.adjust.method="none")
Pairwise comparisons using t tests with pooled SD
data: x and Grp
Yng Med
Med 1.0e-06 -
Old 2.0e-12 2.6e-05
P value adjustment method: none
> t.test(x=x[1:12],y=x[25:36],var.equal=T, alternative="t")
Two Sample t-test
data: x[1:12] and x[25:36]
t = 10.5986, df = 22, p-value = 4.149e-10
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
24.37106 36.22894
sample estimates:
mean of x mean of y
59.34167 29.04167
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