Re: OMEGA BLOCK with mixture model?

Mats, Another difference between BLOCK(2) and DIAG(3) is that they provide different number of ETAs for the individual fit. I am a bit surprised that one-compartment model with random effects on CL, V, and F is identifiable (even with diagonal OMEGA). Indeed, for each subject, this model has 3 free parameters. The only thing that allows to identify them separately is the distributional assumption. It could be rather week so I would expect higher variance values with DIAG(3) versus BLOCK(2). How often have you used ETAs on CL, V, and F in the same one-compartment model (without IV arm)? Is it always stable (or at least as stable as BLOCK(2))? Thanks Leonid -------------------------------------- Leonid Gibiansky, Ph.D. President, QuantPharm LLC web: www.quantpharm.com e-mail: LGibiansky at quantpharm.com tel: (301) 767 5566 Mats Karlsson wrote: > Hi Steve, > > For a one-compartment model I think these are differences: > > 1) DIAG(3) is more restrictive than BLOCK(2) in the sense that only positive > correlation between CL/F and V/F can be estimated > 2) DIAG(3) is less restrictive than BLOCK(2) in the sense that different > transformations can be used for F > 3) DIAG(3) provides an EBE that can be used for diagnostic purposes (DIAG(3) > and BLOCK(2) would give the same estimates for the same model so I don't > understand your comment of var(F) being higher than cov(CL/F,V/F)) > 4) DIAG(3) may facilitate covariate model building (although this is minor > as you with BLOCK(2) can put the same relationship in in two places) > 5) If there truly is a mixture in F1, then I think DIAG(3) has a advantages > over BLOCK(2) in number of parameters (two fewer) needed to describe the > variability model > 6) If some additional assumptions can be reliably made, such as all > variability in F1 is truly in bioavailability and bioavailability is > restricted to be between 0 and 1, some additional info may be extracted from > the data for example by . > > I would not rank any of these as major differences (expect possibly the > mixture aspect which I've never tried). > > For two- or three-compartment models the advantages are that if indeed the > main covariance structure between CL/F, V1/F, Q/F, V2/F is a joint positive > correlation due to variability in bioavailability, fu etc, then a DIAG(5) is > more parsimonious than a BLOCK(4). > > Mats > > Mats Karlsson, PhD > Professor of Pharmacometrics > Dept of Pharmaceutical Biosciences > Uppsala University > Box 591 > 751 24 Uppsala Sweden > phone: +46 18 4714105 > fax: +46 18 471 4003 >