Re: [R] modeling logit(y/n) using lrm

From: Kevin E. Thorpe <kevin.thorpe_at_utoronto.ca>
Date: Sat 17 Jun 2006 - 03:39:15 EST

Hamilton, Cody wrote:
> I have a dataset at a hospital level (as opposed to the patient level)
> that contains number of patients experiencing events (call this number
> y), and the number of patients eligible for such events (call this
> number n). I am trying to model logit(y/n) = XBeta. In SAS this can be
> done in PROC LOGISTIC or GENMOD with a model statement such as: model
> y/n = <predictors>;. Can this be done using lrm from the Hmisc library
> without restructuring the dataset so that for each hospital there is one
> row with y = 1 and one row with y = 0 and then using the weight option
> in lrm to weight these two responses by the number of 'successes' and
> 'failures' for that hospital, respectively? I would like to avoid the
> restructuring, and I understand that the use of the weight function is
> not compatible with a lot of the validation functions available in Hmisc
> (validate, bootcov, etc.).

I don't know about lrm, but for glm you can do glm(cbind(y,m)~ ...) where y is number of successes and m is the number of failures.

So, you might try that.

> Cody Hamilton, Ph.D
>
> Institute for Health Care Research and Improvement
>
> Baylor Health Care System
>
> (214) 265-3618
>

-- 
Kevin E. Thorpe
Biostatistician/Trialist, Knowledge Translation Program
Assistant Professor, Department of Public Health Sciences
Faculty of Medicine, University of Toronto
email: kevin.thorpe@utoronto.ca  Tel: 416.946.8081  Fax: 416.946.3297

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Received on Sat Jun 17 03:52:15 2006

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