Hi, I have to do a multinomial logistic regression on clustedered data. My supervisor ask me to run a logistic regression with robust standard errors in order to take into account dependency between observations in the data set. I have tried to find an appropriate procedure in SAS 9.4 to do so, and my best guess is to use the PROC GLIMMIX in which I put in 'random intercept / subject= id'. However, whwn I do so I get an error in the log saying: 'Nominal model require that the repsonse variable is a group effect on the on RANDOM statements. You need to add 'GROUP=outcome '. When I do so I just get another error saying: 'Model is too large to be fit by PROC GLIMMIX in a resonable amount of time on this system. Consider changing your model.' Then my question is what to do and which model to use? I have used the following SAS syntax: 1st error reported above: PROC GLIMMIX data=c; CLASS age (ref='3') ID; MODEL outcome = age / DIST=multinomial LINK=glogit CL ODDSRATIO; RANDOM intercept / SUBJECT=id; RUN; and 2nd error reported above: PROC GLIMMIX data=c; CLASS age (ref='3') id; MODEL outcome = age / DIST=multinomial LINK=glogit CL ODDSRATIO; RANDOM intercept / SUBJECT=id GROUP=outcome; RUN; Thanks in advance Best, Pernille
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