Conditional weighted residuals (CWRES): A model diagnostic for the FOCE method

Hooker, Andrew C., Staatz, Christine E. and Karlsson, Mats O. (2007) Conditional weighted residuals (CWRES): A model diagnostic for the FOCE method. Pharmaceutical Research, 24 12: 2187-2197. doi:10.1007/s11095-007-9361-x

Author Hooker, Andrew C.
Staatz, Christine E.
Karlsson, Mats O.
Title Conditional weighted residuals (CWRES): A model diagnostic for the FOCE method
Journal name Pharmaceutical Research   Check publisher's open access policy
ISSN 0724-8741
Publication date 2007-01-01
Year available 2007
Sub-type Article (original research)
DOI 10.1007/s11095-007-9361-x
Open Access Status
Volume 24
Issue 12
Start page 2187
End page 2197
Total pages 11
Editor V. H. L. Lee
Place of publication New York, USA
Publisher Springer New York LLC
Language eng
Subject C1
320503 Clinical Pharmacology and Therapeutics
730000 - Health
Formatted abstract
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.
Keyword conditional estimation
weighted residuals
non-linear mixed effect models
model diagnostics
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Excellence in Research Australia (ERA) - Collection
2008 Higher Education Research Data Collection
School of Pharmacy Publications
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Citation counts: TR Web of Science Citation Count  Cited 147 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 150 times in Scopus Article | Citations
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Created: Wed, 23 Apr 2008, 18:37:25 EST by Elizabeth Pyke on behalf of School of Pharmacy