[R] pairwise.t.test vs. t. test

[MARK LEEDS]

thanks. i assumed we we were talking about the standard textbook difference 
between the t test and pairwise t test.
my bad.



----- Original Message ----- 
From: "Chuck Cleland" <ccleland at optonline.net>
To: "MARK LEEDS" <markleeds at verizon.net>
Cc: "Li,Qinghong,ST.LOUIS,Molecular Biology" <Qinghong.Li at rdmo.nestle.com>; 
<r-help at stat.math.ethz.ch>
Sent: Thursday, September 07, 2006 6:44 PM
Subject: Re: [R] pairwise.t.test vs. t. test


> MARK LEEDS wrote:
>> no, because the formula for the test statistics ( even assuming that
>> variances are equal ) of the two different tests are different. in the
>> pairwise t test, the pairwise differences are
>> viewed as one sample so it turns into a one sample test. any intro stat 
>> book
>> will have the formulas.
>>
>>      mark
>
>  Actually, I think the difference is due to the SD being pooled across
> all 3 groups in the pairwise.t.test, but just 2 groups in t.test.
>
>> ----- Original Message ----- 
>> From: "Li,Qinghong,ST.LOUIS,Molecular Biology" 
>> <Qinghong.Li at rdmo.nestle.com>
>> To: <r-help at stat.math.ethz.ch>
>> Sent: Thursday, September 07, 2006 5:07 PM
>> Subject: [R] pairwise.t.test vs. t. test
>>
>>
>>> 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
>>>
>>> [[alternative HTML version deleted]]
>>>
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>>
>> ______________________________________________
>> R-help at stat.math.ethz.ch mailing list
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>> PLEASE do read the posting guide 
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
> -- 
> Chuck Cleland, Ph.D.
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