Optimal design allocations for estimating area under curves for studies employing destructive sampling

Walter W. Piegorsch, A. John Bailer

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Optimal allocations of experimental resources for the estimation of integrals is considered for experiments that use destructive sampling. Given a set of sampling times, a minimum mean square error rule is given for the allotment of fixed experimental resources to the independent variable. The results are seen to be functionally dependent upon the pattern of underlying variability assumed in the model and upon the quadrature rule used to estimate the integral. Extensions to other optimality criteria, including a minimum mean absolute deviation criterion, and to cases involving multiple treatment groups, are also noted.

Original languageEnglish (US)
Pages (from-to)493-507
Number of pages15
JournalJournal of Pharmacokinetics and Biopharmaceutics
Volume17
Issue number4
DOIs
StatePublished - Aug 1989
Externally publishedYes

Keywords

  • mean absolute deviation
  • mean squared error
  • nonlinear experimental design
  • numerical quadrature
  • trapezoidal rule

ASJC Scopus subject areas

  • General Pharmacology, Toxicology and Pharmaceutics
  • Pharmacology (medical)

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