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Conditional weighted residuals (CWRES): a model diagnostic for the FOCE method
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (​Pharmacometrics Research Group)ORCID iD: 0000-0002-2676-5912
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, Division of Pharmacokinetics and Drug Therapy.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences, Division of Pharmacokinetics and Drug Therapy.
2007 (English)In: Pharmaceutical research, ISSN 0724-8741, E-ISSN 1573-904X, Vol. 24, no 12, 2187-2197 p.Article in journal (Refereed) Published
Abstract [en]

Purpose  Population model analyses have shifted from using the first order (FO) to the first-order with conditional estimation (FOCE) approximation to the true model. However, the weighted residuals (WRES), a common diagnostic tool used to test for model misspecification, are calculated using the FO approximation. Utilizing WRES with the FOCE method may lead to misguided model development/evaluation. We present a new diagnostic tool, the conditional weighted residuals (CWRES), which are calculated based on the FOCE approximation. Materials and Methods  CWRES are calculated as the FOCE approximated difference between an individual’s data and the model prediction of that data divided by the root of the covariance of the data given the model. Results  Using real and simulated data the CWRES distributions behave as theoretically expected under the correct model. In contrast, in certain circumstances, the WRES have distributions that greatly deviate from the expected, falsely indicating model misspecification. CWRES/WRES comparisons can also indicate if the FOCE estimation method will improve the results of an FO model fit to data. Conclusions  Utilization of CWRES could improve model development and evaluation and give a more accurate picture of if and when a model is misspecified when using the FO or FOCE methods.

Place, publisher, year, edition, pages
2007. Vol. 24, no 12, 2187-2197 p.
Keyword [en]
Conditional estimation, Model diagnostics, Modeling, Non-linear mixed effect models, NONMEM, Pharmacometrics, Statistics, Weighted residuals
National Category
Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-13617DOI: 10.1007/s11095-007-9361-xISI: 000250722500002PubMedID: 17612795OAI: oai:DiVA.org:uu-13617DiVA: diva2:41387
Available from: 2008-01-24 Created: 2008-01-24 Last updated: 2017-12-11

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Hooker, Andrew C.Karlsson, Mats O

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