[Rd] contr.sum() and contrast names

John Fox jfox at mcmaster.ca
Sat Oct 27 16:44:39 CEST 2012

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.)


John Fox
Sen. William McMaster Prof. of Social Statistics
Department of Sociology
McMaster University
Hamilton, Ontario, Canada
On Sat, 27 Oct 2012 13:39:06 +0200
 Milan Bouchet-Valat <nalimilan at 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
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