R devel - Jul 2008 - matching predictors and dummies

I am trying to make a little web interface for the lm() function. It
calculates both anova F-tests and parameters and returns it in a nice table.
However, I have a problem with matching the Anova predictors with the
regression coefficients: For numeric predictors there is no problem: the
coefficients have the same names as the predictors. However, when a factor
IV is specified, lm() automatically converts this factor to dummy variables,
which (of course) have different names than the orriginal predictor. The lm
model that is returned contains a seperate parameter for every dummy
variable.

Then when you use anova(lm.model) the function seems to know which of the
parameters are dummies of one and the same factor, and takes these together
in the anova-test. The anova() function returns the variance explained by
the orriginal factor, which are all dummies. It does not show the seperate
dummy variables anymore. Of course, this is exactly what you want in an
analysis of variance.

My question is: where in the lm or glm object is stored which of the
parameters are dummies of the same factor? The only thing i could think of
was using lm.model$xlevels, however manipulating these names in the lm-model
did not confuse anova() at all, so I guess there is a better way.

An additional question is if it is possible to specify the names of the
dummy variables that lm/glm creates when a factor is specified as IV? 
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On Fri, 11 Jul 2008, Jeroen Ooms wrote:
>
> I am trying to make a little web interface for the lm() function. It
> calculates both anova F-tests and parameters and returns it in a nice
table.
> However, I have a problem with matching the Anova predictors with the
> regression coefficients: For numeric predictors there is no problem: the
> coefficients have the same names as the predictors. However, when a factor
> IV is specified, lm() automatically converts this factor to dummy
variables,
> which (of course) have different names than the orriginal predictor. The lm
> model that is returned contains a seperate parameter for every dummy
> variable.
>
> Then when you use anova(lm.model) the function seems to know which of the
> parameters are dummies of one and the same factor, and takes these together
> in the anova-test. The anova() function returns the variance explained by
> the orriginal factor, which are all dummies. It does not show the seperate
> dummy variables anymore. Of course, this is exactly what you want in an
> analysis of variance.
>
> My question is: where in the lm or glm object is stored which of the
> parameters are dummies of the same factor? The only thing i could think of
> was using lm.model$xlevels, however manipulating these names in the
lm-model
> did not confuse anova() at all, so I guess there is a better way.
See
 	?terms
 	?terms.object

and run

 	example( terms.object )

or something like

 	terms( lm( Ozone ~ Temp + factor(Month), airquality ) )
>
> An additional question is if it is possible to specify the names of the
> dummy variables that lm/glm creates when a factor is specified as IV?
> --
I'm guessing a custom contrast function would do this. Have a look at

 	?contrasts
 	page( contr.treatment, 'print' )

Or just hack the names attribute of the relevant pieces in the object 
returned by lm/glm.

You do know to use str(), right?


HTH,

Chuck

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> ______________________________________________
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>
Charles C. Berry                            (858) 534-2098
                                             Dept of Family/Preventive Medicine
E mailto:cberry at tajo.ucsd.edu	            UC San Diego
http://famprevmed.ucsd.edu/faculty/cberry/  La Jolla, San Diego 92093-0901

Charles C. Berry wrote:
> 
> See
>  	?terms
>  	?terms.object
> 
> 
> 
I am sorry but i cannot figure out how i can find out which coefficients
belong to which predictors using the model$terms. If i do
attributes(model$terms) i get a nice list which contains the orriginal
factors and some more information, and from model$xlevels i can see the
levels of these factors. However, it does not say anywhere which of the
model$coefficients belong to which factor. The only thing i can imagine is
assuming that the dummy names are simply the concatenation of the factor
name and the level name, which seems to be the default behavior. But
preferebly i would not want to make my program rely on this assumption. How
could i use the model$terms to extract which coefficients belong to which
factor, the way anova() does it?

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