I have a convergence issue in my linear mixed effect model using REPEATED statement in PROC MIXED. It first came up when I used original dependent variable that I later found its problem in normality, so I log transformed the data. After the log transformation, the convergence issue was solved under VC matrix, and I was trying to find the best covariance matrix. Then I realized that not all the matrices converge. I tried VC, UN, CS, AR(1), and TOEP. Only VC, UN, and TOEP converged. I got "WARNING: Stopped because of infinite likelihood." in my output for other matrices. My data has 5 repeated measures, but the number of sample size decreased from 2000+ at baseline to 10 in the last visit. I used the whole data to run the model. That's one thing I can think of that might be related. I tried to exclude the last two visits and there were no problem with convergence. Another thing is that the correlation coefficients are not monotone over repeated measures. I will show a screenshot of correlation matrix from UN so that you can have an idea about it. Here is my code for UN matrix: PROC MIXED DATA=DF METHOD=REML;
CLASS ID FOLLOWUP EXPOSURE;
MODEL OUTCOME_LOG= EXPOSURE FOLLOWUP EXPOSURE*FOLLOWUP / SOLUTION CHISQ DDFM=KR;
REPEATED FOLLOWUP / SUBJECT=ID TYPE=UN R RCORR;
ODS SELECT ModelInfo NObs CorrB ConvergenceStatus FitStatistics;
RUN; The correlation matrix from UN: I still want to keep all visits in the model if possible. Is there any idea of what can possible cause the problem of model not converging and how I can solve it? Thanks in advance!
... View more
