Re: Contrasts

cullisb wrote:
> Dear jason
> in answer to Q2
>
> here is some simple R code to set up a factor with contrasts that you may wish to include in the linear mixed model via the fixed formula argument, I presume.
>
> You can then interact the factor "fff" with any other terms in any way you wish
>
> Note that if you dont specify how.many then R will create a full matrix with the extra column being orthogonal to the mean and the first column and normalised
>
>
> > fff <- factor(c(1,2,3,1,2,3))
> > contrasts(fff) <- matrix(c(-1,1,0),3,1)
> > fff
> >
> [1] 1 2 3 1 2 3
> attr(,"contrasts")
> [,1] [,2]
> 1 -1 -0.4082483
> 2 1 -0.4082483
> 3 0 0.8164966
> Levels: 1 2 3
>
> > contrasts(fff,how.many=1) <- matrix(c(-1,1,0),3,1)
> > fff
> >
> [1] 1 2 3 1 2 3
> attr(,"contrasts")
> [,1]
> 1 -1
> 2 1
> 3 0
> Levels: 1 2 3
>
> HTH
>

Thanks for your help, Brian.
I tried the approach you described, but it seems to me that there is no effect on ASReml-R. In the following simple example, "oats.1" and "oats.2" return the identical results. Did I do something wrong? By contrast, it worked with lm() - see the differences between "oats.x1" and "oats.x2".

Code:
anova(oats.1 <- asreml(fixed=yield ~ Variety, data=oats))
# Df Sum of Sq Wald statistic Pr(Chisq)
# (Intercept) 1 778336 1070 <2e-16 ***
# Variety 2 1786 2 0.2930
# residual (MS) 728

anova(oats.x1 <- lm(yield ~ Variety, data=oats))
# Df Sum Sq Mean Sq F value Pr(>F)
# Variety 2 1786 893 1.2277 0.2993
# Residuals 69 50200 728

contrasts(oats$Variety,how.many=1)<-matrix(c(1,-1,0),3,1)

anova(oats.2 <- asreml(fixed=yield ~ Variety, data=oats))
# Df Sum of Sq Wald statistic Pr(Chisq)
# (Intercept) 1 778336 1070 <2e-16 ***
# Variety 2 1786 2 0.2930
# residual (MS) 728

anova(oats.x2 <- lm(yield ~ Variety, data=oats))
# Df Sum Sq Mean Sq F value Pr(>F)
#Variety 1 336 336 0.4554 0.502
#Residuals 70 51650 738

Jason

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Received on Fri Jul 09 2009 - 00:40:55 EST