Dear NMUsers, I cannot see a reason to leave out the residual error. We all know how error shifts around between IIV, IOV, and residual error. A large residual error is indeed troublesome even when all other model parameters would indicate a good fit with small shrinkage. You only recognize the trouble when you start simulating the kind of responses listed by Andreas. You may have to conclude in the end that your model is not very predictive because of large residual error (=large, still unexplained variability). Joachim Grevel ____________________________________________ AstraZeneca R&D Charnwood Clin. Pharmacology and DMPK Bakewell Road Loughborough, LE11 5RH Tel: +44 1509 64 5177 joachim.gre...@astrazeneca.com
-------------------------------------------------------------------------- AstraZeneca UK Limited is a company incorporated in England and Wales with registered number: 03674842 and a registered office at 15 Stanhope Gate, London W1K 1LN. Confidentiality Notice: This message is private and may contain confidential, proprietary and legally privileged 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 unauthorised use or disclosure of the contents of this message is not permitted and may be unlawful. Disclaimer: Email messages may be subject to delays, interception, non-delivery and unauthorised alterations. Therefore, information expressed in this message is not given or endorsed by AstraZeneca UK Limited unless otherwise notified by an authorised representative independent of this message. No contractual relationship is created by this message by any person unless specifically indicated by agreement in writing other than email. Monitoring: AstraZeneca UK Limited may monitor email traffic data and content for the purposes of the prevention and detection of crime, ensuring the security of our computer systems and checking Compliance with our Code of Conduct and Policies. -----Original Message----- From: owner-nmus...@globomaxnm.com [mailto:owner-nmus...@globomaxnm.com]on Behalf Of andreas lindauer Sent: 07 July 2009 10:34 To: nmusers@globomaxnm.com Subject: [NMusers] Simulations with/without residual error Dear NMUSERS, The recent discussion about simulation with a nonparametric method brought a general question concerning monte-carlo simulations into my mind. When should simulations be performed with residual error and when not. I am especially interested in comments regarding the following scenarios when the result of the simulation should be reported as mean or median and 90% prediction interval: 1. Simulated response at a particular time point (eg. Trough values) 2. Simulated response at a particular time point (x) relative to baseline response (IPRED(t=x)/IPRED(t=0) vs. DV(t=x)/DV(t=0) ) 3. Simulated time of maximal response (eg. Tmax) Thanks and best regards, Andreas. ____________________________ Andreas Lindauer Department of Clinical Pharmacy Institute of Pharmacy University of Bonn An der Immenburg 4 D-53121 Bonn phone: + 49 228 73 5781 fax: + 49 228 73 9757
