Contrasts for lm using contrast package

I'm using contrast package to construct contrasts for lm in R. With the following code I'm making contrast between Trt1 and Trt3.

Y <- c(10, 12, 14, 16, 9, 8)
Trt <- gl(n=3, k=2, length=3*2)
Data1 <- data.frame(Y, Trt)

Data1.lm <- lm(Y~Trt, data = Data1)

library(contrast)
Contrs1 <- contrast(Data1.lm, a=list(Trt="1"), b=list(Trt="3"), type = "average")
print(Contrs1, X=TRUE)

I'd like to make a contrast between the average of (Trt1 and Trt2) and Trt3. I used this code

Contrs2 <- contrast(Data1.lm, a=list(Trt="1", Trt="2"), b=list(Trt="3"), type = "average")
print(Contrs2, X=TRUE)

lm model parameter contrast

  Contrast     S.E.    Lower    Upper    t df Pr(>|t|)
1      6.5 1.224745 2.602315 10.39768 5.31  3   0.0131

Contrast coefficients:
  (Intercept) Trt2 Trt3
1           0    1   -1

I can see that this is not the desired contrast. I wonder how to get the correct contrast with the contrast package in R.

P.S. I know to do use the contrast matrix for aov function in R but for this particular problem I want to use contrast package.

Solution

You should specify the included treatment levels as a vector (Trt=c("1","2")), not a list. I figured this out by looking at the examples in ?contrast.lm (although admittedly it helps to know what you're looking for):

Contrs2 <- contrast(Data1.lm, a=list(Trt=c("1","2")), b=list(Trt="3"),
                    type = "average")
print(Contrs2, X=TRUE)
## lm model parameter contrast
##   Contrast    S.E.    Lower    Upper    t df Pr(>|t|)
## 1      4.5 1.06066 1.124506 7.875494 4.24  3    0.024