[R] Re-Post: Combining Factors in model.matrix

[Paul Boutros]

> On Sat, 24 Jan 2004 paul.boutros at utoronto.ca wrote:
>
> > I didn't get any response on this before, leading me to believe
> > I've missed
> > something fundamental.  Can anybody guide me in the correct
> > direction for more help on this?

Thanks for your reply:

> You will need to explain to us why the object you list is `the design
> matrix': have *you* a reference for that?  R is doing the conventional
> thing, and I at least have no idea where your example comes from.

Perhaps I have used the wrong terminology?  My understanding of a design
matrix is that it identifies the factors are present for a given experiment.

Here, I have a two factor experiment, where each factor has two levels.
In the case I gave:
   t1 t2
1   1  0
2   1  1
3   0  0
4   0  1

I had expected this to represent four distinct experiments where
factor one is present in the first two and absent in the second two.

> You seem to have coded variables t1 and t2 the opposite ways (the
> reference level is 2 for t1 and 1 for t2), and your model has the fit at
> levels t1=2,t1=1 constrained to pass through the origin.  I don't think R
> has a simple syntax for that (although you can fake anything), and I find
> it hard to believe that is actually what you want.

That wasn't my intention, I want to retain the intercept term and
not constrain it to pass through the origin.

Paul

> >
> > Paul
> >
> > =================================================
> > I want to be able to create a design matrix with two factors.
> For instance, if
> > I have:
> >
> > > t1 <- factor(c(1,1,2,2));
> > > t2 <- factor(c(1,2,1,2));
> > > design <- model.matrix(~ -1 + (t1+t2));
> > > design;
> >   t11 t12 t22
> > 1   1   0   0
> > 2   1   0   1
> > 3   0   1   0
> > 4   0   1   1
> >
> > But the design matrix I want is:
> >    t1 t2
> > 1   1  0
> > 2   1  1
> > 3   0  0
> > 4   0  1
> >
> > Actually, in general I'm struggling with the syntax for
> formulating a design
> > matrix I can write down on paper.  Is there a reference for
> this beyond the R
> > documentation?
>
> Chapter 6 of MASS has the most complete exposition (by Bill
> Venables) that
> I know of, and the White Book (Chambers & Hastie, 1992) goes well beyind
> the R documentation (which uses it as the reference).
>
> --
> Brian D. Ripley,                  ripley at stats.ox.ac.uk
> Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
> University of Oxford,             Tel:  +44 1865 272861 (self)
> 1 South Parks Road,                     +44 1865 272866 (PA)
> Oxford OX1 3TG, UK                Fax:  +44 1865 272595
>