R help - Jan 2016 - Order of terms and model.matrix()

Hello,

It is not very clear to me from the model.matrix documentation, why simply
changing the order of terms in the formula may give a different design
matrix.  Please note I?m purposely not including main effects in the model
formulae.

set.seed(1)
x1 <- rnorm(100)
f1 <- factor(sample(letters[1:3], 100, replace = TRUE))
trt <- sample(c(-1,1), 100, replace = TRUE)
df <- data.frame(y=y, x1=x1, f1=f1, trt=trt)

head(model.matrix( ~ x1:trt + f1:trt, data = df))
(Intercept)      x1:trt trt:f1b trt:f1c
1           1 -0.62036668       1       0
2           1  0.04211587       0       0
3           1 -0.91092165       0       1
4           1  0.15802877       0       1
5           1  0.65458464       0      -1
6           1  1.76728727       0       1

head(model.matrix(~ f1:trt + x1:trt, data = df)) #terms reversed
(Intercept) f1a:trt f1b:trt f1c:trt      trt:x1
1           1       0       1       0 -0.62036668
2           1       1       0       0  0.04211587
3           1       0       0       1 -0.91092165
4           1       0       0       1  0.15802877
5           1       0       0      -1  0.65458464
6           1       0       0       1  1.76728727

Thanks,
Axel.

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