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- Title
Parametric and nonparametric population methods: their comparative performance in analysing a clinical dataset and two Monte Carlo simulation studies.
- Authors
Bustad, Aida; Terziivanov, Dimiter; Leary, Robert; Port, Ruediger; Schumitzky, Alan; Jelliffe, Roger
- Abstract
This study examined parametric and nonparametric population modelling methods in three different analyses. The first analysis was of a real, although small, clinical dataset from 17 patients receiving intramuscular amikacin. The second analysis was of a Monte Carlo simulation study in which the populations ranged from 25 to 800 subjects, the model parameter distributions were Gaussian and all the simulated parameter values of the subjects were exactly known prior to the analysis. The third analysis was again of a Monte Carlo study in which the exactly known population sample consisted of a unimodal Gaussian distribution for the apparent volume of distribution (V(d)), but a bimodal distribution for the elimination rate constant (k(e)), simulating rapid and slow eliminators of a drug.
- Publication
Clinical pharmacokinetics, 2006, Vol 45, Issue 4, p365
- ISSN
0312-5963
- Publication type
Journal Article
- DOI
10.2165/00003088-200645040-00003