My model has several independent and categorical variables. I would not like
to subset them as other variables in the data are useful. I just wanted to
set some coefficients for some levels in a single category.
A prototype of it can be something like y + constant *
(cat.variable1-Level1) ~ x1 + x2 + cat.variable1(if level != level1) +
cat.variable2 +....

Currently, I am modifying data by creating new variables for each level and
recoding the original values.

I am wondering if there are any other approaches.

Thanks,
Danda

On Sun, Nov 29, 2009 at 11:48 AM, David Winsemius <dwinsemius@comcast.net>wrote:

>
> On Nov 29, 2009, at 11:23 AM, sr danda wrote:
>
>  Hi,
>>
>> I am a new R user. I am using it develop regression models with
>> categorical
>> variables.
>> Is there a way to force some regression coefficients to be zero for some
>> of
>> the values in a categorical variable (with 12 factor levels)?
>>
>> I am recoding the values to the default value (1st in the order of
>> dummy's).
>> But I am not sure if this is the correct approach if I want to force
>> coefficients to be specific values.
>>
>
> It's a bit unclear from your description what you are trying to do (and it
> might help to hear the justification for doing it). If you do not want the
> cases with particular factor levels used in the prediction, then subset them
> out. If you want a group of factor levels grouped and and then used as the
> reference level, then perhaps:
>
> ?relevel
>
> That will of course result in the intercept term becoming the adjusted mean
> for those levels, but I'm sure you already knew that.
>
>
>
>> Thanks for your help.
>>
>> Regards,
>> Danda
>>
>>  --
>
> David Winsemius, MD
> Heritage Laboratories
> West Hartford, CT
>
>

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