On Sun, 17 Jan 2016, Lars Bishop wrote:
I’d appreciate your help on understanding the following.
It is not very clear to me from the model.matrix documentation, why
simply changing the order of terms in the formula may change the number
of resulting columns. Please note I’m purposely not including main
effects in the model formula in this case.
IIRC, there are some heuristics involved harking back to the White Book. I
recall there have been discussions of whether and how this could be fixed
before on this list and or R-devel, but I cannot seem to lay my browser on
them right now.
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(x1=x1, f1=f1, trt=trt)
dim(model.matrix( ~ x1:trt + f1:trt, data = df))
[1] 100 4
dim(model.matrix(~ f1:trt + x1:trt, data = df))
[1] 100 5
By `x1:trt' I guess you mean the same thing as `I(x1*trt)'.
If you use the latter form, the issue you raise goes away.
Note that `I(some.expr)' gives you the ability to force the behavior of
model.matrix to be exactly what you want by suitably crafting `some.expr',
heuristics notwithstanding.
HTH,
Chuck
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