From: "Joern Loetsch" j.loetsch@em.uni-frankfurt.de Subject: [NMusers] MIXTURE modeling Date: Thu, 17 Nov 2005 11:29:13 +0100 Dear NONMEM users, I am working on a mixture model and would be grateful for some advice. I have a one-compartment model with first-order absorption, and get two subpopulations with different CL, the same Ka (factor almost equal to one between the Ka's of the two subpopulations, and A value of V that varies in one subpopulation but is almost the same for all subjects in the second subpopulation (very low ETA in that subpopulation). Questions: 1. Can I join the Ka's to have only one THETA(Ka) for both subpopulation? 2. How do I identify co-variates? Same procedure as without MIX, only separately for the two subpopulations? 3. The objective function went down by 55.14 from the model without covariates and without MIX, but the subpopulations do not appear meaningful. This applies also to the quite high (as compared to the estimate without MIX) volume of distribution that does not vary interindividually in one subpopulation. How do I deal with this result. Thank you in advance for your advice. Sincerely J. Lötsch _______________________________________________ Prof. Dr. med. Jörn Lötsch pharmazentrum frankfurt/ZAFES Institut für Klinische Pharmakologie Johann Wolfgang Goethe-Universität Theodor-Stern-Kai 7 D-60590 Frankfurt am Main Tel.:069-6301-4589 Fax.:069-6301-7636 http://www.klinik.uni-frankfurt.de/zpharm/klin/ _______________________________________________________ From: "Gobburu, Jogarao V" GOBBURUJ@cder.fda.gov Subject: RE: [NMusers] MIXTURE modeling Date: Thu, 17 Nov 2005 06:17:25 -0500 Hello, please see my responses below: 0. First of all, I am not sure what prompted you to apply a mixture model and how rich the data are. 1. You do not have to estimate different modes for the two populations for all the parameters. You should limit it to the ones that you think are reasonable, ie., you need some prior expectation (eg: poor vs fast metabolizers) or graphical evidence. 2. Covariate selection should be similar with or without MIX. However, it would be important to explore if one or several of the covariates can explain the mixture. 3. Bruce Green and Nick Holford presented some work on using log-likelihood ratios to select mixture models at the Annual AAPS meeting last week (asymptotic vs. empirical via re-randomization tests). They show that the estimation method (FO vs FOCE) makes a big difference. They may have more to add on this. Regarding volume for one of the sub-pops, do you have adequate data to estimate this parameter? Regards, Joga _______________________________________________________ From: "Bruce Green" greenb@pharmacy.uq.edu.au Subject: RE: [NMusers] MIXTURE modeling Date: Fri, 18 Nov 2005 09:52:22 +1000 Hi Joern, Mixture models can be useful if you can clearly identify two subpopulations by just looking at the data. However, relying on the dOBJ as a diagnostic for the presence of a mixture is probably not a good idea, especially if you are using the FO method. We identified that the delta OBJ might be really large (in the magnitude of thousands) to reject the null. Which method in NONMEM are you using, what sort of error structure do you have? Cheers, Bruce _______________________________________________________