[R] how to create model matrix of second order terms

[Bert Gunter]

Full disclosure: I did not attempt to decipher your code.

But ~(A+B +C)^2 - (A + B + C)
gives all 2nd order interactions whether the terms are factors or numeric.

~I(A^2) + I(B^2) gives quadratics in A and B, which must be numeric, not
factors, of course

You can combine these as necessary to get a formula expression for just 2nd
order terms. Wrapping this in model.matrix() should then give you the model
matrix using "treatment" contrasts for the contrasts involving factors (you
can change the contrast types using the 'contrasts.arg' argument of
model.matrix())

1. Does this help?
2. Do check this to make sure I'm correct

Cheers,
Bert

"An educated person is one who can entertain new ideas, entertain others,
and entertain herself."



On Mon, Mar 24, 2025 at 12:22 AM Stephen Bond via R-help <
r-help using r-project.org> wrote:

> I am sending to this forum as stackoverflow has devolved into sth
> pretty bad.
> Below code shows how to get what I want in a clumsy way.
>
> cols <- letters[1:4]
> a1 <- outer(cols,cols,paste0)
> b1 <- a1[!lower.tri(a1)]
>
> X <- matrix(rnorm(80),ncol=4)
> colnames(X) <- cols
> X <- as.data.frame(X)
> XX <- matrix(0,nrow=nrow(X),ncol=length(b1))
> colnames(XX) <- b1
>
> for (k in 1:length(b1)){
>     XX[,k] <- X[,substr(b1[k],1,1)]*X[,substr(b1[k],2,2)]
> }
>
>
>
> Is there a way to get that using a formula or some neat trick? The
> above will not work for factors, so I will need to create the factor
> crossings using formula a*b*c and then cross with the numerics, which
> is even more clumsy.
> Thanks everybody
>
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