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

[Kevin E. Thorpe]

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 at utoronto.ca  Tel: 416.946.8081  Fax: 416.946.3297