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: [EMAIL PROTECTED] Tel: 416.946.8081 Fax: 416.946.3297 ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
