Mitsuo, This is a new message specific to NONMEM VI. I must confess I don't know what to make of this message myself. It would be informative if someone could tell us what internals in NONMEM trigger this message (i.e., "PROBLEMS OCCURRED WITH THE MINIMIZATION").
With respect to your two model runs note that they are really two different parameterizations. In the first parameterization, where TVCL = THETA(1) * THETA(2) ** SEX note that THETA(1) represents the true value of CL for males and THETA(2) represents the ratio of CL between females to males. In the second parameterization, where TVCL = THETA(1) IF (SEX.EQ.1) TVCL = THETA(2) note that THETA(1) and THETA(2) represent the true values of CL for males and females, respectively. Thus, THETA(2) has a different interpretation between these two parameterizations. A third parameterization that you could consider is TVCL = THETA(1) *(1 + THETA(2))**SEX or equivalently, TVCL = THETA(1) * (1 + THETA(2)*SEX) where THETA(1) is again the true value of CL for males and THETA(2) is the fractional change in CL for females relative to males. Each of these parameterizations should result in the same model fit (i.e., minimum value of the OFV) but one parameterization may be more stable than another...it is similar to the issue with continuous covariates where we center or scale the covariate based on the mean or median value (i.e., centering or scaling will reduce the correlation in the estimates between the intercept term and the covariate effect which should lead to a more stable model and faster convergence to the minimum OFV). I would look at the COV step output and in particular, look at the correlation of the estimates between THETA(1) and THETA(2) for these different parameterizations. My guess is that the correlation is higher for the first parameterization (given that you indicate that it gives this warning message and that the second parameterization does not). You can also use the PRINT=E option on the COV statement and look at the ratio of the largest to the smallest eigenvalues to more globally assess the stability of your model. In the end, if they all converge to the same final OFV and if you really want to estimate the ratio of CLs between males and females then so be it even if the model is less stable and NONMEM gives you this warning message. On the other hand, if the different parameterizations don't converge to the same OFV then you need to look more closely at how you parameterize the covariate effect. If you get a lower OFV with the second parameterization because it is more stable and NONMEM has an easier time iterating to the minimum OFV then I would go with that parameterization and if you want to estimate the ratio of the CLs you can always estimate it as THETA(2)/THETA(1) (i.e., which is equivalent to THETA(2) in the first parameterization. I hope this helps. Ken Kenneth G. Kowalski President & CEO A2PG - Ann Arbor Pharmacometrics Group, Inc. 110 E. Miller Ave., Garden Suite Ann Arbor, MI 48104 Work: 734-274-8255 Cell: 248-207-5082 Fax: 734-913-0230 [EMAIL PROTECTED] -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Higashimori, Mitsuo Sent: Wednesday, November 12, 2008 10:06 PM To: nmusers@globomaxnm.com Subject: [NMusers] NONMEM message Dear all, I have a following error(?) massage on a poplation analysis using NONMEM VI. 0MINIMIZATION SUCCESSFUL HOWEVER, PROBLEMS OCCURRED WITH THE MINIMIZATION. REGARD THE RESULTS OF THE ESTIMATION STEP CAREFULLY, AND ACCEPT THEM ONLY AFTER CHECKING THAT THE COVARIANCE STEP PRODUCES REASONABLE OUTPUT. I found it when I described a control stream to assess sex difference on oral clearance as shown in below, TVCL = THETA(1) * THETA(2) ** SEX where SEX=0 for male and SEX=1 for female. This message was displayed without any error message. It was not dissapeared even though I changed the initial parameters. However, it was solved when I changed the model definition. For example, TVCL = THETA(1) IF (SEX.EQ.1) TVCL = THETA(2) Could you please let me know some details regarding the message. Especially, I'd like to know 1. What impact does this error message give the analysis result? 2. Why does it depend on the model definition? Thanks, _/ _/ _/ Mitsuo Higashimori, Ph.D. _/ _/ _/ Pharmacokinetic Group, Early Phase Development Department _/ _/ _/ Clinical Division, Research & Development _/ _/ _/ AstraZeneca K.K. _/ _/ _/ E-mail: [EMAIL PROTECTED]
