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

[Peter Dalgaard]

"Kevin E. Thorpe" <kevin.thorpe at utoronto.ca> writes:

> 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.

  glm(y/n~..., binomial, weight=n....)

should work as well. I suspect that this passes trough to lrm, too.

> 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 at utoronto.ca  Tel: 416.946.8081  Fax: 416.946.3297
> 
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