Dear Pascal,
What you observed is related to “speed” of estimation. With a larger dataset (many dummies) you slow down the estimation. Roughly similar to using the SLOW command in $EST. With an estimation that has difficulties to converge you see a difference in EBEs and other parameters. We saw the same when we compared runs on installations with different CPU speed. My recommendation: do not restart with $MSFI but run from non-optimised initial estimates as you did with the original data set. Anyway, the differences you saw are probably within the range you would also find if you did a bootstrap. Good luck, Joachim Joachim Grevel, PhD Scientific Director BAST Inc Limited Loughborough Innovation Centre Charnwood Building Holywell Park, Ashby Road Loughborough, LE11 3AQ Tel: +44 (0)1509 222908 Confidentiality Notice: This message is private and may contain confidential and proprietary information. If you have received this message in error, please notify us and remove it from your system and note that you must not copy, distribute or take any action in reliance on it. Any unauthorized use or disclosure of the contents of this message is not permitted and may be unlawful. From: owner-nmus...@globomaxnm.com [mailto:owner-nmus...@globomaxnm.com] On Behalf Of pascal.gir...@merckgroup.com Sent: 23 November 2012 16:09 To: nmusers@globomaxnm.com Subject: [NMusers] Different EBE estimation between original and enriched dataset with MDV=1 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 pascal.gir...@merckgroup.com 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.
