> > > 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. > > The design matrix is X in the regression usually represented by > > y = Xb + e > > and is called a model matrix in S/R.
Right, that's how I understood it. > > 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 can't have factors that are present/absent. (You can have levels of > treatments which are present/absent.) We understand the rows to represent > the individuals runs of a single experiment, but what do the columns > represent? Yes, I mis-spoke. I thought the columns represent individual factors, with a 0 = level 1 for this factor 1 = level 2 for this factor Hence the encoding I gave above would indicate that factor 1 is at level 1 for the first pair of experiments, but at level 0 for the second pair. > > > 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. > > So why did you use ~ -1 + (t1+t2) ? That explicitly removes the > intercept. Ahh, I had misunderstood the -1 as explicitly specifying an intercept. So now: > t1 <- factor(c(1,1,2,2)); > t2 <- factor(c(1,2,1,2)); > design <- model.matrix(~ t1+t2); > design; (Intercept) t12 t22 1 1 0 0 2 1 0 1 3 1 1 0 4 1 1 1 Which is what I had been looking for! Thank you for your patient help, Paul ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html