Hi Milan, Take a look at the contr.Sum() and contr.Treatment() functions in the car package.
(I recall, BTW, the sometimes acrimonious previous discussion of this issue.) Best, John ------------------------------------------------ John Fox Sen. William McMaster Prof. of Social Statistics Department of Sociology McMaster University Hamilton, Ontario, Canada http://socserv.mcmaster.ca/jfox/ On Sat, 27 Oct 2012 13:39:06 +0200 Milan Bouchet-Valat <nalimi...@club.fr> wrote: > Hi! > > I would like to suggest to make it possible, in one way or another, to > get meaningful contrast names when using contr.sum(). Currently, when > using contr.treatment(), one gets factor levels as contrast names; but > when using contr.sum(), contrasts are merely numbered, which is not > practical and can lead to mistakes (see code at the end of this > message). > > This issue was discussed quickly in 2005 by Brian Ripley in a reply to a > message on R-help [1]. He rightly stressed that treatment and sum > contrasts are not equivalent to levels of a factor, because one needs to > know the reference (here, level or sum) to interpret them. But when one > knows the type of contrasts that are being used, useful labels are still > of high value. I don't think anybody does serious work with sum > contrasts named myfactor1, myfactor2, myfactor3. (This reasoning does > not so much apply to contr.helmert() since ordered factors can quite > naturally be reported using numbers.) > > Thus, would it be possible to add an option to contr.sum() so that it > returns a matrix whose column names are the levels of the input factor? > Such an option could also be added to other contrasts with default to > FALSE. Another solution, which could be even more practical, would be to > add a new function, called for example contr.sum2(), which would do the > same thing - after all, we already have contr.SAS() to implement a > slightly different behavior while being essentially the same as > contr.treatment(). > > This contr.sum() issue really sounds like a detail, but it's sad one > given that factors work really great in R in all other situations. The > only reason I can think of to explain this behavior is that people > rarely use it. When fitting log-linear models with glm(), for example, > this contrast is the most natural one, but currently gives poorly named > coefficients when everything could be so easy to interpret if factor > levels were used. This means people have to implement a replacement for > contr.sum() by hand, which is not the end of the world but is definitely > not optimal given how simple the solution is. > > Thanks for your attention! > > > Illustration of the current difference between contr.sum() and > contr.treatment(): > > > z <- factor(LETTERS[1:3]) > > contr.treatment(z) > B C > A 0 0 > B 1 0 > C 0 1 > > contr.sum(z) > [,1] [,2] > A 1 0 > B 0 1 > C -1 -1 > > 1: https://stat.ethz.ch/pipermail/r-help/2005-July/075430.html > > ______________________________________________ > R-devel@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-devel ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
