Using some simulated data:
> A <- rnorm(7, mean=1); B <- rnorm(9, mean=2); C <- rnorm(13,
mean=2.5)
> y <- c(A, B, C)
> f <- factor(rep(1:3, c(7, 9, 13)))
> TukeyHSD(aov(y~f))
Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = y ~ f)
$f
diff lwr upr
2-1 0.9345966 -0.2173612 2.086554
3-1 1.5357566 0.4641358 2.607377
3-2 0.6011600 -0.3900490 1.592369
HTH,
Andy
> -----Original Message-----
> From: Anna H. Pryor [mailto:anna at ptolemy.arc.nasa.gov]
> Sent: Wednesday, August 13, 2003 9:28 AM
> To: R-help mailing list
> Subject: [R] anova and tukeyHSD
>
>
>
> I would like to do a one way anova and then a tukeyHSD. I
> have three vectors
> A,B and C. In a previous help message, I was told to do the
> following for
> the anova:
>
> y = c(A,B,C)
> group = factor(rep(a:3,c(7,9,13))) #provided there a 7
> elements in A,9 in B
> and 13 in C
>
> and then
>
> anova(lm(y~group))
>
>
> Looking at the tukeyHSD method it looks like it wants the aov
> method which I
> don't understand. Using the above example, could someone
> continue the
> example and get the tukeyHSD method to work?
>
> Anna
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://www.stat.math.ethz.ch/mailman/listinfo> /r-help
>
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