R help - Jun 2024 - Column names of model.matrix's output with contrast.arg

Dear list,

Changing the default contrasts used in glm() makes me aware how model.matrix()
set column names.

With default contrasts, model.matrix() use the level values to name the columns.
However with other contrasts, model.matrix() use the level indexes. In the
documentation, I don?t see anything in the documentation related to this ? It
does not seem natural to have such a behavior?

Any comment is welcome.

An example is below.

Kind regards, Christophe  


#example from ?glm
counts <- c(18,17,15,20,10,20,25,13,12)
outcome <- paste0("O", gl(3,1,9))
treatment <- paste0("T", gl(3,3))

X3 <- model.matrix(counts ~ outcome + treatment)
X4 <- model.matrix(counts ~ outcome + treatment, contrasts =
list("outcome"="contr.sum"))
X5 <- model.matrix(counts ~ outcome + treatment, contrasts =
list("outcome"="contr.helmert"))

#check with original factor
cbind.data.frame(X3, outcome)
cbind.data.frame(X4, outcome)
cbind.data.frame(X5, outcome)

#same issue with glm
glm.D93 <- glm(counts ~ outcome + treatment, family = poisson())
glm.D94 <- glm(counts ~ outcome + treatment, family = poisson(), contrasts =
list("outcome"="contr.sum"))
glm.D95 <- glm(counts ~ outcome + treatment, family = poisson(), contrasts =
list("outcome"="contr.helmert"))

coef(glm.D93)
coef(glm.D94)
coef(glm.D95)

#check linear predictor
cbind(X3 %*% coef(glm.D93), predict(glm.D93))
cbind(X4 %*% coef(glm.D94), predict(glm.D94))

-------------------------------------------------
Christophe DUTANG
LJK, Ensimag, Grenoble INP, UGA, France
ILB research fellow
Web: http://dutangc.free.fr

You're at the mercy of the various contr.XXX functions. They may or may not
set the colnames on the matrices that they generate.

The rationales for (not) setting them is not perfectly transparent, but you
obviously cannot use level names on contr.poly, so it uses .L, .Q, etc.

In MASS, contr.sdif is careful about labeling the columns with the levels that
are being diff'ed.

For contr.treatment, there is a straightforward connection to 0/1 dummy
variables, so level names there are natural.

One could use levels in contr.sum and contr.helmert, but it might confuse users
that comparisons are with the average of all levels or preceding levels. (It can
be quite confusing when coding is +1 for male and -1 for female, so that the
gender difference is twice the coefficient.)

-pd
> On 14 Jun 2024, at 08:12 , Christophe Dutang <dutangc at gmail.com>
wrote:
> 
> Dear list,
> 
> Changing the default contrasts used in glm() makes me aware how
model.matrix() set column names.
> 
> With default contrasts, model.matrix() use the level values to name the
columns. However with other contrasts, model.matrix() use the level indexes. In
the documentation, I don?t see anything in the documentation related to this ?
It does not seem natural to have such a behavior?
> 
> Any comment is welcome.
> 
> An example is below.
> 
> Kind regards, Christophe  
> 
> 
> #example from ?glm
> counts <- c(18,17,15,20,10,20,25,13,12)
> outcome <- paste0("O", gl(3,1,9))
> treatment <- paste0("T", gl(3,3))
> 
> X3 <- model.matrix(counts ~ outcome + treatment)
> X4 <- model.matrix(counts ~ outcome + treatment, contrasts =
list("outcome"="contr.sum"))
> X5 <- model.matrix(counts ~ outcome + treatment, contrasts =
list("outcome"="contr.helmert"))
> 
> #check with original factor
> cbind.data.frame(X3, outcome)
> cbind.data.frame(X4, outcome)
> cbind.data.frame(X5, outcome)
> 
> #same issue with glm
> glm.D93 <- glm(counts ~ outcome + treatment, family = poisson())
> glm.D94 <- glm(counts ~ outcome + treatment, family = poisson(),
contrasts = list("outcome"="contr.sum"))
> glm.D95 <- glm(counts ~ outcome + treatment, family = poisson(),
contrasts = list("outcome"="contr.helmert"))
> 
> coef(glm.D93)
> coef(glm.D94)
> coef(glm.D95)
> 
> #check linear predictor
> cbind(X3 %*% coef(glm.D93), predict(glm.D93))
> cbind(X4 %*% coef(glm.D94), predict(glm.D94))
> 
> -------------------------------------------------
> Christophe DUTANG
> LJK, Ensimag, Grenoble INP, UGA, France
> ILB research fellow
> Web: http://dutangc.free.fr
> 
> ______________________________________________
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-- 
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
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Email: pd.mes at cbs.dk  Priv: PDalgd at gmail.com