03-29-2018 12:05 PM
I have several clinical data set with binary response. For all data sets, subjects are enrolled from different sites and are taking either treatment A or B (parallel design). I am trying to assess the site variation for the response variable. Since there are 2 treatment, I assume that the site variation could be different for the 2 treatments and there could be a correlation. The following is my SAS code:
proc glimmix data=dset;
class sitenum trt;
model resp= trt/dist=bin link=logit solution;
random trt/SUBJECT=SITENUM type=UN solution G;
For most data sets, Proc Glimmix doesn't converge. For one data set, Glimmix does converge and I got the following covariance matrix. I think here 0.00907 is the site variance of treatment A and 3.54E-18 is the site variance of treatment B. However, the covariance between treatments A and B are even bigger than the both variance, so the correlation will be >1. Do I understand it correct? I don't know why it can happened.
|Estimated G Matrix|
|Effect||Description of Actual Arm||Row||Col1||Col2|
03-29-2018 04:38 PM
I am a little confused by:
For most data sets, Proc Glimmix doesn't converge
I would expect that you would combine all of the data to have all of the sites in one data set to answer a question about the impact of "site" on the analysis. Why are these separate data sets analyzed one a time? Are you comparing all pairs of individual sites?
04-02-2018 01:34 PM