[R] Creating dummy vars with contrasts - why does the returned identity matrix contain all levels (and not n-1 levels) ?

[David Winsemius]

On Sep 13, 2013, at 9:33 AM, E Joffe wrote:

> Thank you so much for your answer  !
> As far as I understand, glmnet doesn't accept categorical variables  
> only
> binary factors - so I had to create dummy variables for all  
> categorical
> variables.
> It worked perfectly.

It's not exactly clear what worked perfectly. Since glmnet will only  
accept a matrix as its `x` data input, did you use model.matrix to  
construct the "dummies" and cbind your numeric predictors to that  
result? If you just assigned a factor attribute, it's more likely that  
you didn't actually use "dummies" but rather regressed on the integer  
values of the factor.

-- 
David.

-- 
> Erel
>
>
> Erel Joffe MD MSc
> School of Biomedical Informatics
> University of Texas - Health Science Center in Houston
> 832.287.0829 (c)
>
> -----Original Message-----
> From: David Winsemius [mailto:dwinsemius at comcast.net]
> Sent: Friday, September 13, 2013 3:05 PM
> To: E Joffe
> Cc: r-help at r-project.org
> Subject: Re: [R] Creating dummy vars with contrasts - why does the  
> returned
> identity matrix contain all levels (and not n-1 levels) ?
>
>
> On Sep 13, 2013, at 4:15 AM, E Joffe wrote:
>
>> Hello,
>>
>>
>>
>> I have a problem with creating an identity matrix for glmnet by using
>> the contrasts function.
>
> Why do you want to do this?
>
>> I have a factor with 4 levels.
>>
>> When I create dummy variables I think there should be n-1 variables
>> (in this case 3) - so that the contrasts would be against the  
>> baseline
>> level.
>>
>> This is also what is written in the help file for 'contrasts'.
>>
>> The problem is that the function creates a matrix with n variables
>> (i.e. the same as the number of levels) and not n-1 (where I would
>> have a baseline level for comparison).
>
> Only if you specify contrasts=FALSE does it do so and this is  
> documented in
> that help file.
>>
>>
>>
>> My questions are:
>>
>> 1.       How can I create a matrix with n-1 dummy vars ?
>
> See below.
>
>> was I supposed to
>> define explicitly that I want contr.treatment (contrasts) ?
>
> No need to do so.
>
>>
>> 2.       If it is not possible, how should I interpret the hazard
>> ratios in
>> the Cox regression I am generating (I use glmnet for variable
>> selection and
>> then generate a Cox regression)  - That is, if I get an HR of 3 for
>> the
>> variable 300mg what does it mean ? the hazard is 3 times higher of
>> what ?
>>
>
> Relative hazards are generally referenced to the "baseline hazard",
> i.e. the hazard for a group with the omitted level for treatment
> constrasts and the mean value for any numeric predictors.
>
>> Here is some code to reproduce the issue:
>>
>> # Create a 4 level example factor
>>
>> trt <- factor( sample( c("PLACEBO", "300 MG", "600 MG", "1200 MG"),
>>
>>                      100, replace=TRUE ) )
>
> # If your intent is to use constrasts different than the defaults used
> by
> #  regression functions, these factor contrasts need to be assigned,
> either
> # within the construction of the factor or after the fact.
>
>> contrasts(trt)
>         300 MG 600 MG PLACEBO
> 1200 MG      0      0       0
> 300 MG       1      0       0
> 600 MG       0      1       0
> PLACEBO      0      0       1
>
> # the default value for the contrasts parameter is TRUE and the
> default type is treatement
>
> # That did not cause any change to the 'trt'-object:
> trt
>
> #To make a change you need to use the `contrasts<-` function:
>
> contrasts (trt) <- contrasts(trt)
> trt
>
>>
>> # Use contrasts to get the identity matrix of dummy variables to be
>> used in
>> glmnet
>>
>> trt2 <- contrasts (trt,contrasts=FALSE)
>>
>> Results (as you can see all levels are represented in the identity
>> matrix):
>>
>>> levels (trt)
>> [1] "1200 MG" "300 MG"  "600 MG"  "PLACEBO"
>>
>>
>>> print (trt2)
>>
>>       1200 MG 300 MG 600 MG PLACEBO
>>
>> 1200 MG       1      0      0       0
>>
>> 300 MG        0      1      0       0
>>
>> 600 MG        0      0      1       0
>>
>> PLACEBO       0      0      0       1
>>
>>
>>
>> 	[[alternative HTML version deleted]]
>
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>
> -- 
> David Winsemius, MD
> Alameda, CA, USA
>
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David Winsemius, MD
Alameda, CA, USA