Hello, I would like to create a plot where I have categories in the x-axis (e.g. race, region, etc.) and the rate of an event (e.g. death,) of a binary response variable on the y-axis. To me this almost seems like plotting the row percent for the "event occured" column in na Rx2 frequency table. If anyone can give me some guidance on how to best go about this, I would really appreciate it. Thanks! ... View more

Hello, I am using proc GLIMMIX to develop a model for mortality by a specified time-point (binary outcome of alive or dead at 30-days). The data are clustered by hospital so I am using PROC GLIMMIX to fit a random intercept model for the data using the reporting hospital as the subject variable. In order to properly evaluate the performance of my models I would like to examine their calibration and discrimination. I found this article (41364 - ROC analysis for binary response models fit in the GLIMMIX, NLMIXED, GAM or other procedures) detailing how to create an ROC curve and get a c-statistic (i.e. area under the ROC curve) for examining model discrimination; however, I am still having problems figuring out how to get a good measure of calibration. Proc GLIMMIX does not have the LACKFIT option to produce a Hosmer-Lemeshow statistic as in Proc Logistic (and I am fairly certain that this statistic is not appropriate to use with clustered data anyway). I am trying to figure out how to do something along the lines of producing a "plot of expected vs. observed mortality rates across deciles of increasing risk" but am having some trouble figuring out how to go about doing this. Any help you could provide woul dbe greatly appreciated. Thank you! ... View more