[R] Re-Post: Combining Factors in model.matrix
Paul Boutros
Paul.Boutros at utoronto.ca
Mon Jan 26 08:30:57 CET 2004
> 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
>
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