OMEGA BLOCK with mixture model?

Dear all, I am trying to fit a PK model to oral data. In the data, we observed two things: First, CL seems to be negatively correlated with F1. Secondly, there seem to be two subpopulations in the exposure, let's say a large group with 'normal' and a second group with high exposure. I would like to identify the subpopulations using a mixture model, but keep the correlation between CL and F1. Now I ran into problems when coding the $OMEGA BLOCK. I figured the block to be something like: $OMEGA BLOCK(3) 0.1 ;CL1 0 FIX 0.1 ;CL2 0.01 0.01 0.1 ;F1 The error message that appears is: a covariance is zero, but the block is not a band matrix I assume that this means that I am not allowed to fix the correlation between the two clearance-omegas to zero. However, it would be unreasonable to allow a correlation, because the omegas belong to different subpopulations, so there can't be a correlation. On the other hand, I did not include subpopulations for F1, so how can I keep this correlation to both CL-subgroups? Any thoughts on this would be highly appreciated! Best wishes Nele ______________________________________________________________ Dr. Nele Plock Pharmacometrics -- Modeling and Simulation Nycomed GmbH Byk-Gulden-Str. 2 D-78467 Konstanz, Germany Fon: (+49) 7531 / 84 - 4759 Fax: (+49) 7531 / 84 - 94759 mailto: [email protected] http://www.nycomed.com County Court: Freiburg, Commercial Register HRB 701257 Chairman Supervisory Board: Charles Depasse Management Board: Dr. Barthold Piening, Gilbert Rademacher, Dr. Anders Ullman ---------------------------------------------------------------------- Proprietary or confidential information belonging to Nycomed Group may be contained in this message. If you are not the addressee indicated in this message, please do not copy or deliver this message to anyone. In such case, please destroy this message and notify the sender by reply e-mail. Please advise the sender immediately if you or your employer do not consent to Internet e-mail for messages of this kind. Opinions, conclusions and other information in this message that pertain to the sender's employer and its products and services represent the opinion of the sender and do not necessarily represent or reflect the views and opinions of the employer.