Concordance between criteria for covariate model building

Hennig, Stefanie and Karlsson, Mats (2014) Concordance between criteria for covariate model building. Journal of Pharmacokinetics And Pharmacodynamics, 41 2: 109-125. doi:10.1007/s10928-014-9350-8

Author Hennig, Stefanie
Karlsson, Mats
Title Concordance between criteria for covariate model building
Journal name Journal of Pharmacokinetics And Pharmacodynamics   Check publisher's open access policy
ISSN 1567-567X
Publication date 2014-01-01
Year available 2014
Sub-type Article (original research)
DOI 10.1007/s10928-014-9350-8
Open Access Status DOI
Volume 41
Issue 2
Start page 109
End page 125
Total pages 17
Place of publication New York, NY United States
Publisher Springer New York LLC
Language eng
Formatted abstract
When performing a population pharmacokinetic modelling analysis covariates are often added to the model. Such additions are often justified by improved goodness of fit and/or decreased in unexplained (random) parameter variability. Increased goodness of fit is most commonly measured by the decrease in the objective function value. Parameter variability can be defined as the sum of unexplained (random) and explained (predictable) variability. Increase in magnitude of explained parameter variability could be another possible criterion for judging improvement in the model. The agreement between these three criteria in diagnosing covariate-parameter relationships of different strengths and nature using stochastic simulations and estimations as well as assessing covariate-parameter relationships in four previously published real data examples were explored. Total estimated parameter variability was found to vary with the number of covariates introduced on the parameter. In the simulated examples and two real examples, the parameter variability increased with increasing number of included covariates. For the other real examples parameter variability decreased or did not change systematically with the addition of covariates. The three criteria were highly correlated, with the decrease in unexplained variability being more closely associated with changes in objective function values than increases in explained parameter variability were. The often used assumption that inclusion of covariates in models only shifts unexplained parameter variability to explained parameter variability appears not to be true, which may have implications for modelling decisions. 
Keyword Covariates
Parameter variability
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
School of Pharmacy Publications
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Citation counts: TR Web of Science Citation Count  Cited 3 times in Thomson Reuters Web of Science Article | Citations
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Created: Fri, 21 Feb 2014, 06:28:41 EST by Dr Stefanie Hennig on behalf of School of Pharmacy