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

From: Hamilton, Cody <CodyH_at_baylorhealth.edu>
Date: Sat 17 Jun 2006 - 03:31:38 EST

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.).

Cody Hamilton, Ph.D

Institute for Health Care Research and Improvement

Baylor Health Care System

(214) 265-3618

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