
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





This e-mail, facsimile, or letter and any files or attachments transmitted with it contains information that is confidential and privileged. This information is intended only for the use of the individual(s) and entity(ies) to whom it is addressed. If you are the intended recipient, further disclosures are prohibited without proper authorization. If you are not the intended recipient, any disclosure, copying, printing, or use of this information is strictly prohibited and possibly a violation of federal or state law and regulations. If you have received this information in error, please notify Baylor Health Care System immediately at 1-866-402-1661 or via e-mail at privacy@baylorhealth.edu. Baylor Health Care System, its subsidiaries, and affiliates hereby claim all applicable privileges related to this information.
	[[alternative HTML version deleted]]

