David.
On Nov 29, 2009, at 4:09 PM, sr danda wrote:
> 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 at 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
>
>
David Winsemius, MD
Heritage Laboratories
West Hartford, CT