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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