I found the solution:
http://stats.stackexchange.com/questions/12993/how-to-setup-and-interpret-anova-contrasts-with-the-car-package-in-r
Sorry for the trouble.
On Sun, Mar 24, 2013 at 8:58 PM, Erin Hodgess <erinm.hodg...@gmail.com>wrote:
> Dear R People:
>
> I have the following in a file:
>
> resp factA factB
> 39.5 low B-
> 38.6 high B-
> 27.2 low B+
> 24.6 high B+
> 43.1 low B-
> 39.5 high B-
> 23.2 low B+
> 24.2 high B+
> 45.2 low B-
> 33.0 high B-
> 24.8 low B+
> 22.2 high B+
>
> and I construct the data frame:
>
> > collard.df <- read.table("collard.txt",header=TRUE)
> > collard.aov <- aov(resp~factA*factB,data=collard.df)
> > summary(collard.aov)
> Df Sum Sq Mean Sq F value Pr(>F)
> factA 1 36.4 36.4 5.511 0.0469 *
> factB 1 716.1 716.1 108.419 6.27e-06 ***
> factA:factB 1 13.0 13.0 1.971 0.1979
> Residuals 8 52.8 6.6
> ---
> Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1
> > tapply(collard.df$resp,list(collard.df$factA,collard.df$factB),mean)
> B- B+
> high 37.03333 23.66667
> low 42.60000 25.06667
> >
>
> Fair enough. Let's pretend for a second that interaction existed. Then I
> want to set up contrasts such that mean(high) - mean(low) = 0 and mean(B+)
> - mean(B-) = 0.
>
> I know that this is really simple, but I've tried all kinds of things with
> glht and am not sure that I'm on the right track. Sorry for the trouble
> for the simple question.
>
> Thanks,
> erin
>
>
>
>
> --
> Erin Hodgess
> Associate Professor
> Department of Computer and Mathematical Sciences
> University of Houston - Downtown
> mailto: erinm.hodg...@gmail.com
--
Erin Hodgess
Associate Professor
Department of Computer and Mathematical Sciences
University of Houston - Downtown
mailto: erinm.hodg...@gmail.com
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