Hi Leonid, I would not use my quite limited tests for any conclusions with respect to precision or convergence properties of coding #1. NONMEM definitively reported warnings with both FOCE(I) and SAEM/IMP runs and both runs proceeded to optimize the model parameters. The paths of optimization and number of iterations were different. The final estimates differed from the runs that used coding #2. The fit was not terribly different across runs but, as you said, more impact may be observed when the covariates change more drastically.
Based upon Bob's response, it is interesting to think that individuals with time varying discrete covariates would not be considered as being part of one category or another, under coding #1, but as weighted average of each category they can belong to... Sebastien Regeneron - Internal ________________________________ From: Leonid Gibiansky <lgibian...@quantpharm.com> Sent: Friday, January 10, 2025 8:21 PM To: Sébastien Bihorel <sebastien.biho...@regeneron.com>; nmusers@globomaxnm.com <nmusers@globomaxnm.com> Subject: [External] Re: [NMusers] MU referencing and time-varying covariates Hi Sébastien, As you did these experiments, can you share the results: have you seen any differences in the fit, parameter estimates, precision, convergence speed (number of iteration), and evaluation time for SAEM/IMP (I think, FOCEI does not EXTERNAL MESSAGE _________________________________________________________________ Hi Sébastien, As you did these experiments, can you share the results: have you seen any differences in the fit, parameter estimates, precision, convergence speed (number of iteration), and evaluation time for SAEM/IMP (I think, FOCEI does not have this restriction of time-independence even if you use Mu referencing, so results should be identical or very close). As code is encrypted, only Bob can answer the question but my understanding is that some kind of averaging is used to get time independent value of WT that is then used by the SAEM/IMP algorithm for parameter update procedure. As WT changes slowly and not very significantly, it could be hard to see the differences. A more stringent test would be to use time-dependent and strongly influential ADA (0/1): how bad is the incorrect version 1 in this case? Thank you Leonid On 1/10/2025 2:56 PM, Sébastien Bihorel wrote: > > Happy New Year, > > I hope everybody is ready for a great 2025 ! > > I'll start my message/question by defining 2 different ways of coding a > simple power relationship between body weigh on clearance. > > * > Coding 1 > > MU_1 = THETA(1) + THETA(2) * LOG(WGT/70) > CL = EXP( MU_1 + ETA(1) ) > > * > Coding 2 > > MU_1 = THETA(1) > CL = EXP( MU_1 + ETA(1) ) * ( WGT/70 )**THETA(2) > > The reference and training materials for NONMEM clearly indicate that MU > variables should be time invariant within occasions and recommend using > coding 2 when body weight is time varying. Nevertheless, it is possible > for an analyst to use coding 1. As far as I can tell from some limited > testing, this is not a "fatal" error. Either with FOCE(I) or SAEM/IMP, > NONMEM reports a warning but performs the model optimization. The table > outputs also report CL as a time varying variable changing as body > weight changes. > > So my questions are the following: when coding 1 is used and body weight > is time varying, what is NONMEM actually doing during model > optimization? Does NONMEM internally create occasions to break the > records by interval of constant body weight and constant MU1? > Alternatively, does NONMEM internally calculate an average of MU1? > Something entirely different? What's the risk taken by an analyst when > using coding 1 versus coding 2? > > Thank you in advance for you input > > > __ > Sébastien Bihorel > Director, Quantitative Pharmacology > +1 914-648-9581 > sebastien.biho...@regeneron.com > > > Regeneron - Internal > > ******************************************************************** > This e-mail and any attachment hereto, is intended only for use by the > addressee(s) named above and may contain legally privileged and/or > confidential information. 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