I guess I didn't explain it well enough.

I have a number of training examples.  They have 4 fields.
label, v1, v2, group

The label is binary ("yes", "no")

My  understanding (Quite possible wrong.) was that there was a way to 
train the LR to estimate probabilities "per group"

In pseudo-code it would be:
lrm( label ~ v1 + v2, group_by(group)

-N




On 8/4/09 3:41 PM, David Winsemius wrote:
>
> On Aug 4, 2009, at 6:38 PM, Noah Silverman wrote:
>
>> Thanks David,
>>
>> But HOW do I indicate the "grouping" variable in the formula?
>
> Hard to tell. You have told us absolutely nothing about the problem. 
> Discrete variables cause no problems in formulas. Perhaps one of :
>
> ?factor
> ?cut
> ?quantile
>
>>
>> Thanks!
>>
>> -N
>>
>> On 8/4/09 3:37 PM, David Winsemius wrote:
>>>
>>> On Aug 4, 2009, at 6:33 PM, Noah Silverman wrote:
>>>
>>>> Hi,
>>>>
>>>> Trying to setup a logistic regression model.  (Something new to me. I
>>>> usually use SVM.)
>>>>
>>>> The person explaining the concept explained to me that I can include a
>>>> "group" variable so that the probabilities predicted by the model will
>>>> be "per group"
>>>>
>>>> Does this make sense to anyone?
>>>
>>> Yes.
>>>
>>>> If so, how would I implement this?
>>>> Using the glm or lrm function?
>>>
>>> Yes.
>>>
>
> David Winsemius, MD
> Heritage Laboratories
> West Hartford, CT
>

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