[R] Qualitative factors

[vito muggeo]

There are several ways to model categorical variables, including
corner-point, sum-zero, helmert,....

In R you can select them using the options() function, namely for instance

options(contrasts = c(unordered = "contr.treatment", ordered =
"contr.poly"))

or directly in the model
lm(y~x+C(m, treatment)) or lm(y~x+C(m, sum)) and so on.

The interpretation of the estimated coefficients (and their univariate Wald
statistic) depends on the used parameterization, but the LRT does not.

best,
vito


----- Original Message -----
From: "ZABALZA-MEZGHANI Isabelle" <Isabelle.zabalza-mezghani at IFP.fr>
To: "help R (E-mail)" <r-help at stat.math.ethz.ch>
Cc: "JOURDAN Astrid" <Astrid.JOURDAN at IFP.fr>
Sent: Thursday, November 07, 2002 9:55 AM
Subject: [R] Qualitative factors


> Hi,
> I have some doubt about how qualitative factors are coded in R. For
> instance, I consider a response y, a quantitative factor x and a
qualitative
> factor m at 3 levels, generated as follow :
>
> y_c(6,4,2.3,5,3.5,4,1.,8.5,4.3,5.6,2.3,4.1,2.5,8.4,7.4)
> x_c(3,1,3,1,2,1,4,5,1,3,4,2,5,4,3)
> m_gl(3,5)
>
> lm(y~x+m)
>
> Coefficients:
> (Intercept)            x           m2           m3
>     3.96364      0.09818      0.44145      0.62291
>
> In literature, 2 usual implicit coding process are suggested : m1=0 or
> m1=-m2-m3. Does R use one of these process ? (I've already read the R
> documentation on this topic, and it is still not clear in my mind).
> Furthermore, how can I make prediction using this model, I mean how should
I
> specify the new data (especially for m).
>
> Thanks in advance for your help
>
> Regards,
>
> Isabelle Zabalza-Mezghani
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