Re: 2-compartment model: V2 doesn't vary

From: Lewis B Sheiner <lewis@c255.ucsf.edu> Subject: Re: 2-compartment model: V2 doesn't vary Date: Mon, 01 Oct 2001 07:02:06 -0700 This has been discussed many times on nmusers - see archive. Basically, it is impossible to distinguish multiple components of variance when data are sparse. Maximum Likelihood (not NONMEM) prefers to drive certain variances to zero if they are unidentifiable. This is a peculiarity of ML. It does not mean that there is no variability in V2; it simply means that variability on V1, CL, etc., is adequate to explain the variability in the data. If you are using FO, it may be possible to estimate additional variance components by using FOCE, but that is inevitable. LBS.