Estimation and inference in pharmacokinetic models: The effectiveness of model reformulation and resampling methods for functions of parameters Journal Article


Authors: Niedzwiecki, D.; Simonoff, J. S.
Article Title: Estimation and inference in pharmacokinetic models: The effectiveness of model reformulation and resampling methods for functions of parameters
Abstract: It is well known that high parameter estimate correlations and asymptotic variance estimates can cause estimation and inference problems in the analysis of pharmacokinetic models. In this paper we show that analysis of three important functions of pharmacokinetic parameters, the half-life, mean residence time, and the area under the curve, can sometimes be greatly improved by reformulating the model to address collinearity and by using the bootstrap to form confidence intervals. The resultant estimators can be more accurate than the original ones, and resultant confidence intervals can be narrower. Of the three measures, the half-life estimator is much better behaved than the estimators of mean residence time and area under the curve under collinearity, suggesting that it (or measures like it) should be used more often. © 1990 Plenum Publishing Corporation.
Keywords: methodology; models, biological; computer simulation; analysis of variance; mathematical computing; pharmacokinetic modeling; theoretical study; pharmacokinetics; bootstrap; article; collinearity; nonlinear estimation
Journal Title: Journal of Pharmacokinetics and Biopharmaceutics
Volume: 18
Issue: 4
ISSN: 0090-466X
Publisher: Plenum Press  
Date Published: 1990-08-01
Start Page: 361
End Page: 377
Language: English
DOI: 10.1007/bf01062274
PUBMED: 2231325
PROVIDER: scopus
DOI/URL:
Notes: Article -- Export Date: 27 January 2020 -- Source: Scopus
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