Re: Cross-validation script in NM

Dear Pieter, If your end goal is to perform k-fold cross-validation, you can use PsN's crossval program. It is run with commands like crossval mymodel.mod -groups=5 where mymodel.mod is any regular estimation-type control stream. This will perform 'groups'-fold cross-validation. The prediction models are copies of the estimation models, except that $DATA is changed, initial estimates are automatically set to final estimates from the estimations, and MAXEVAL is set to 0 (or corresponding for non-classical estimation methods). $PK will be identical, so there should be no problem with time-varying covariates. Just make sure to delete the run folder after you have retrieved the results, because it will be very large. Best regards, Kajsa On 12/04/2014 06:03 PM, Pieter Colin wrote: Dear nm-users, I’m trying to construct a NONMEM control file to be used in a cross-validation study. In a first problem statement I run an estimation step on a subset of my data. In a subsequent problem statement (within the same control file) I am trying to predict the PK of the subset that was not included in part 1. I managed to do this by use of the MSFO option (in the first part of the control file) and the $MSFI in de second part. However, it appears that time-varying covariates (defined under $PK in the first problem statement) are not evaluated when performing the predictions for the second problem statement. Does anyone know of a workaround for this or is there another way of combining a fit and predict action (both on different data) within the same control-file? Kind regards, Pieter -- Pieter Colin, Pharm.D., Ph.D. Post-Doctoral researcher (Faculty of Pharmaceutical Sciences – Ghent University) Associate Professor (Department of Anesthesiology – UMCG) -- ----------------------------------------------------------------- Kajsa Harling, PhD System Developer Department of Pharmaceutical Biosciences Uppsala University [email protected] +46-(0)18-471 4308 http://www.farmbio.uu.se/research/researchgroups/pharmacometrics/