It would help to know more about the data set, but with 9.2 you can do the
same analyses with GLIMMIX:
PROC GLIMMIX method=laplace ; * or method= quad;
model count = lnW / dist=poisson solution;
random int / subject=id;
And you might start with dist=negbin, or at least compare the results.
That the NLMIXED is not converging could be due to a number of reasons,
though knowing more about what data are like that go into the proc -- how
many id's, excess 0's? small counts, etc. -- helps one to better
understand what does or does not come out of it.
03/09/2010 12:34 PM
SAS nlmixed for count data with random effect
"SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
I am trying to estimate a very simple model with a small twist. Counts
are distributed by Poisson arrival rate, along with a normal
proc nlmixed data=countdata;
parms logsig 0 alpha1 1 beta1 1;
eta = (alpha1 + beta1*lnW)+ e;
lambda = exp(eta);
model count ~ poisson(lambda);
random e ~ normal(0,exp(2*logsig)) subject=id;
I get the error "Optimization cannot be completed". How can this model
be suitably reimplemented in NLMIXED? Should I be looking at some
other procedure? Appreciate any comment.