RE: RES and WRES output with Beal's M3 method

Dear Sebastien and NONMEM users, It is correct that NONMEM doesn't return any RES or WRES for individuals who have at least one observation with F_FLAG=1. It is understandable that NONMEM can't return residuals for the BQL observations (F_FLAG=1) since PRED is a likelihood in this case and not a prediction (furthermore the observation is an interval and can neither be used to calculate a residual). However, I don't understand why it doesn't do so for the observations for which F_FLAG=0? Can this be considered a bug? You can of course always get out individual residuals (IRES) and individual weighted residuals (IWRES) (below this paragraph you can see my definition of IWRES). What you can do if you really want to get RES and WRES is to run a MAXEVAL=0 run with your final estimates. The BQL data should in this case be omitted (or set to a fix value) and all M3 code taken out. Remember in this case that the IRES and IWRES and other EBE dependent variables will not be correct following the MAXEVAL=0 run (i.e. use only the PRED, RES and WRES out of this run and the rest from your original fit with the M3 code). In case you are using the FOCE estimation method you would preferably want to look at conditional weighted residuals (CWRES) rather than WRES. However I have yet not seen any example of a workaround to get these when using the M3 method (Obs! CWRES will not be correctly calculated with the MAXEVAL=0 trick). $ERROR IPRED = F W = THETA(11) ; SD for additive residual error ; W = THETA(11) * IPRED ; SD for proportional residual error ; W = SQRT(THEATA(11)**2+THETA(12)**2*IPRED**2) ; SD for combined residual error Y = IPRED + W*EPS(1) IRES = DV - IPRED IWRES = IRES/W $SIGMA 1 FIX If you use Xpose to do your diagnostic plots it can be good to know that Xpose by default omits all rows with WRES=0 (this is done to omit information on dosing row from being plotted). You can change this setting in Xpose by using the command inclZeroWRES=TRUE (you should then enter some other subset to omit the dose rows e.g. subset="EVID==0"). My favorite type of diagnostics are VPCs (I think I share this with Prof. Nick Holford). VPCs can easily be adopted to handle the presence of BQL data. How to do this with PsN and Xpose is explained in a PAGE poster from 2009 ( http://www.page-meeting.org/pdf_assets/7002-Poster_PAGE_VPC_090618_final.pd f). Best regards, Martin Bergstrand, MSc, PhD student ----------------------------------------------- Pharmacometrics Research Group, Department of Pharmaceutical Biosciences, Uppsala University ----------------------------------------------- [email protected] ----------------------------------------------- Work: +46 18 471 4639 Mobile: +46 709 994 396 Fax: +46 18 471 4003