I worry whether you understand what is happening when you lump all the "unwanted levels" into a reference level. Be sure to watch the intercept as you compare models. It will be some sort of adjusted mean for whatever cases are in the reference levels of that and teh reference levels of any other factor. It will change as you add or remove levels from that status. Just because you get no coefficient does not mean those data points are not affecting the predictions you will make from the model. The prediction for cases in those reference levels will NOT be 0. Nor will the predicted differences between that group and others be zero.

--
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 <dwinsem...@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

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