On 3/6/2010 4:38 PM, casperyc wrote:> Hi,
>
> I am trying to reproduce a tukey test in R
>
> =========================> x=c(145,40,40,120,180,
> 140,155,90,160,95,
> 195,150,205,110,160,
> 45,40,195,65,145,
> 195,230,115,235,225,
> 120,55,50,80,45
> )
> y2=c(
> rep(as.character(1),5),
> rep(as.character(2),5),
> rep(as.character(3),5),
> rep(as.character(4),5),
> rep(as.character(5),5),
> rep(as.character(6),5)
> )
>
> crd2=data.frame(x,y2)
>
> model1=aov(x~y2,data=crd2)
> TukeyHSD(model1)
>
> =========================>
> The result in the 'diff' of the means are the same as those did
using SAS,
> (which is in my tutorial sheet, i got a MAC, so cant use SAS)
> however, the 95% confiden limits are quite different.
>
> ==========================>
> 2-1 23 -73.817441 119.817441 0.975518208
> 3-1 59 -37.817441 155.817441 0.435116628
> 4-1 -7 -103.817441 89.817441 0.999912318
> 5-1 95 -1.817441 191.817441 0.056613465
> 6-1 -35 -131.817441 61.817441 0.869242006
> 3-2 36 -60.817441 132.817441 0.855531189
> 4-2 -30 -126.817441 66.817441 0.926612938
> 5-2 72 -24.817441 168.817441 0.232896275
> 6-2 -58 -154.817441 38.817441 0.453535553
> 4-3 -66 -162.817441 30.817441 0.316718292
> 5-3 36 -60.817441 132.817441 0.855531189
> 6-3 -94 -190.817441 2.817441 0.060579795
> 5-4 102 5.182559 198.817441 0.034819938
> 6-4 -28 -124.817441 68.817441 0.944203446
> 6-5 -130 -226.817441 -33.182559 0.004294761
>
> ==========================>
> in the SAS output, it's
> (in slightly different order, you can just check one of the set)
> ==========================> 5 - 3 36.00 -28.63 100.63
> 5 - 2 72.00 7.37 136.63 ***
> 5 - 1 95.00 30.37 159.63 ***
> 5 - 4 102.00 37.37 166.63 ***
> 5 - 6 130.00 65.37 194.63 ***
> 3 - 5 -36.00 -100.63 28.63
> 3 - 2 36.00 -28.63 100.63
> 3 - 1 59.00 -5.63 123.63
> 3 - 4 66.00 1.37 130.63 ***
> 3 - 6 94.00 29.37 158.63 ***
> 2 - 5 -72.00 -136.63 -7.37 ***
> 2 - 3 -36.00 -100.63 28.63
> 2 - 1 23.00 -41.63 87.63
> 2 - 4 30.00 -34.63 94.63
> 2 - 6 58.00 -6.63 122.63
> 1 - 5 -95.00 -159.63 -30.37 ***
> 1 - 3 -59.00 -123.63 5.63
> 1 - 2 -23.00 -87.63 41.63
> 1 - 4 7.00 -57.63 71.63
> 1 - 6 35.00 -29.63 99.63
> 4 - 5 -102.00 -166.63 -37.37 ***
> 4 - 3 -66.00 -130.63 -1.37 ***
> 4 - 2 -30.00 -94.63 34.63
> 4 - 1 -7.00 -71.63 57.63
> 4 - 6 28.00 -36.63 92.63
> 6 - 5 -130.00 -194.63 -65.37 ***
> 6 - 3 -94.00 -158.63 -29.37 ***
> 6 - 2 -58.00 -122.63 6.63
> 6 - 1 -35.00 -99.63 29.63
> 6 - 4 -28.00 -92.63 36.63
> ==========================>
> say, betweet treatment 5 and 3
>
> R
> 5-3 36 -60.817441 132.817441
> SAS
> 5-3 36 -28.63 100.63
>
> i am wondering if i have done something wrong in R?
It looks like the confidence intervals for your SAS output are not
family-wise intervals. For example, you can get intervals that match
your SAS output when you don't adjust for multiple comparisons.
> confint(lm(x ~ as.factor(y2), data=crd2))
2.5 % 97.5 %
(Intercept) 59.302005 150.69800
as.factor(y2)2 -41.626725 87.62672
as.factor(y2)3 -5.626725 123.62672
as.factor(y2)4 -71.626725 57.62672
as.factor(y2)5 30.373275 159.62672
as.factor(y2)6 -99.626725 29.62672
> full documents are in the attachment,
> can someone suggest to me the relevent R codes
> that does the same sort of thing?
> (tukeyHSD,fisherLSD,and anova table )
>
> Thanks!
>
> casper http://n4.nabble.com/file/n1583109/SAS.pdf SAS.pdf
> http://n4.nabble.com/file/n1583109/R.pdf R.pdf
> http://n4.nabble.com/file/n1583109/ws1.pdf ws1.pdf
> http://n4.nabble.com/file/n1583109/ws1sols.pdf ws1sols.pdf
--
Chuck Cleland, Ph.D.
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