Re: Different EBE estimation between original and enriched dataset with MDV=1

On Nov 23, 2012, at 12:57 PM, "Leonid Gibiansky" <[email protected]> wrote: > Hi Pascal, > I think the problem is in the precision of the integration routine. With > extra points, you change the ODE integration process and the results. I would > use TOL=10 or higher in the original estimation. I have seen cases when > changing TOL from 6 to 0 or 10 changed the outcome quite significantly. > Leonid > > -------------------------------------- > Leonid Gibiansky, Ph.D. > President, QuantPharm LLC > web: www.quantpharm.com > e-mail: LGibiansky at quantpharm.com > tel: (301) 767 5566 > > > > On 11/23/2012 11:08 AM, [email protected] wrote: >> Dear NM-User community, >> >> I have a model with 2 differential equations and I use ADVAN6 TOL=5. In >> $DES, I am using T the continuous time variable. The run converges, $COV >> is OK, and the model gives a reasonable fit. In order to compute some >> statistics which cannot be obtained analytically, I need to compute >> individual predictions based on individual POSTHOC parameters and an >> extended grid of time for interpolating the observed times. >> >> So I have >> 1) added to my original dataset extra points regularly spaced with >> MDV=1. To give you an idea, my average observation time is 25, with a >> range going from 5 to 160. So my grid was set so that I have a dummy >> observation every 1 unit of time. >> 2) rerun my model using $MSFI to initialize the pop parameters, with >> MAXEVAL=0 and POSTHOC options so that individual empirical Bayes >> estimates (EBE) parameters for each patient would be first re-estimated, >> then the prediction would be computed. >> >> Then I >> 3) checked that my new predictions computed from the extended dataset >> match the predictions of the original dataset at observed time points. I >> had the surprise to see that for some individuals those predictions >> match, for some others they slightly diverge, and for few others they >> are dramatically different. I checked the EBEs and they were clearly >> different between the original dataset and the one with the dummy points. >> 4) I decided to redo the grid with only one dummy point every 1/4 of >> time unit. The result was less dramatic, but still for most of my >> individuals the EBEs predictions were diverging from the original ones >> computed without the dummy times. >> >> Of course the solution for me is to estimate the EBEs from the original >> dataset, export them in a table and reread them to initialize the >> parameter of my individuals using only dummy time points and no >> observations. >> >> This problem reminds me something that was discussed previously on >> nm-user, but I could not recover the source in the archive. >> >> Anyway is this something known and predictable that when adding dummy >> points with MDV=1 to your original dataset you sometimes get very >> different EBEs ? Are there cases/models/ADVAN where the problem is >> likely to happen? Is their a way to fix it it in NONMEM other than the >> trick I used? >> >> Thanks for your replies! >> >> Kind regards, >> >> Pascal Girard, PhD >> [email protected] >> Head of Modeling & Simulation - Oncology >> Global Exploratory Medicine >> Merck Serono S.A. · Geneva >> Tel: +41.22.414.3549 >> Cell: +41.79.508.7898 >> >> This message and any attachment are confidential and may be privileged >> or otherwise protected from disclosure. If you are not the intended >> recipient, you must not copy this message or attachment or disclose the >> contents to any other person. If you have received this transmission in >> error, please notify the sender immediately and delete the message and >> any attachment from your system. Merck KGaA, Darmstadt, Germany and any >> of its subsidiaries do not accept liability for any omissions or errors >> in this message which may arise as a result of E-Mail-transmission or >> for damages resulting from any unauthorized changes of the content of >> this message and any attachment thereto. Merck KGaA, Darmstadt, Germany >> and any of its subsidiaries do not guarantee that this message is free >> of viruses and does not accept liability for any damages caused by any >> virus transmitted therewith. >> >> Click _ http://www.merckgroup.com/disclaimer_to access the German, >> French, Spanish and Portuguese versions of this disclaimer.