[R] Contrast specified with C() - R vs S-Plus problem

[Pascal A. Niklaus]

Thanks for the reply. Below is the solution and the S-Plus and R code
that does the same (for documentation).

>I can't reproduce that in S-PLUS 6.1, and it is not as documented:
>  
>
In S-Plus 2000, C() complements the contrast matrix with orthogonal 
contrasts if only the first is given.

> CO2 <- factor(rep(c("A","C","E"),each=8))

> m <- rep(seq(0,3,length=8),3) + rep(c(0,1,2),each=8)

> summary.aov(aov(m ~ C(CO2,c(1,0,-1))))

                    Df Sum of Sq  Mean Sq  F Value       Pr(F)

C(CO2, c(1, 0, -1))  2  16.00000 8.000000 7.259259 0.004013532

          Residuals 21  23.14286 1.102041

> summary.lm(aov(m ~ C(CO2,c(1,0,-1))))

Coefficients:

                        Value Std. Error  t value Pr(>|t|)

         (Intercept)   2.5000   0.2143    11.6667   0.0000

C(CO2, c(1, 0, -1))1  -1.0000   0.2624    -3.8103   0.0010

C(CO2, c(1, 0, -1))2   0.0000   0.3712     0.0000   1.0000

Residual standard error: 1.05 on 21 degrees of freedom

Multiple R-Squared: 0.4088

F-statistic: 7.259 on 2 and 21 degrees of freedom, the p-value is 0.004014

Correlation of Coefficients:

                     (Intercept) C(CO2, c(1, 0, -1))1

C(CO2, c(1, 0, -1))1 0

C(CO2, c(1, 0, -1))2 0           0


In the meanwhile, I found that the same can be done in R like this:

> library(gregmisc)

> CO2 <- factor(rep(c("A","C","E"),each=8))

> m <- rep(seq(0,3,length=8),3) + rep(c(0,1,2),each=8)

> contrastsCO2 <- rbind("A vs E"=c(1,0,-1))

> a <- aov(m ~ CO2, contrasts=list( CO2=make.contrasts(contrastsCO2)))

> summary(a)

            Df Sum Sq Mean Sq F value   Pr(>F)

CO2          2 16.000   8.000  7.2593 0.004014 **

Residuals   21 23.143   1.102

> summary.lm(a)

Coefficients:

              Estimate Std. Error  t value Pr(>|t|)

(Intercept)  2.500e+00  2.143e-01    11.67 1.22e-10 ***

CO2A vs E   -2.000e+00  5.249e-01    -3.81  0.00102 **

CO2C2        9.774e-17  3.712e-01 2.63e-16  1.00000

---

Signif. codes:  0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1

Residual standard error: 1.05 on 21 degrees of freedom

Multiple R-Squared: 0.4088,     Adjusted R-squared: 0.3525

F-statistic: 7.259 on 2 and 21 DF,  p-value: 0.004014