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microsamplingDesign
View on CRAN: Click
here
Download and install microsamplingDesign package within the R console
Install from CRAN:
install.packages("microsamplingDesign")
Install from Github:
library("remotes")
install_github("cran/microsamplingDesign")
Install by package version:
library("remotes")
install_version("microsamplingDesign", "1.0.8")
Attach the package and use:
library("microsamplingDesign")
Maintained by
Adriaan Blommaert
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-05-02
Latest Update: 2021-10-13
Description:
Find optimal microsampling designs for non-compartmental pharacokinetic analysis using a general simulation methodology:
Algorithm III of Barnett, Helen, Helena Geys, Tom Jacobs, and Thomas Jaki. (2017) "Optimal Designs for Non-Compartmental
Analysis of Pharmacokinetic Studies. (currently unpublished)"
This methodology consist of (1) specifying a pharmacokinetic model
including variability among animals; (2) generating possible sampling times; (3)
evaluating performance of each time point choice on simulated data; (4)
generating possible schemes given a time point choice and additional constraints
and finally (5) evaluating scheme performance on simulated data. The default
settings differ from the article of Barnett and others, in the default pharmacokinetic model used and
the parameterization of variability among animals. Details can be found in the package vignette. A 'shiny'
web application is included, which guides users from model parametrization to
optimal microsampling scheme.
How to cite:
Adriaan Blommaert (2018). microsamplingDesign: Finding Optimal Microsampling Designs for Non-Compartmental
Pharmacokinetic Analysis. R package version 1.0.8, https://cran.r-project.org/web/packages/microsamplingDesign. Accessed 04 Jan. 2025.
Previous versions and publish date:
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Functions, R codes and Examples using
the microsamplingDesign R package
Some associated functions: PkData-class . PkModel-class . PkModelParent-class . PkModelRange-class . SetOfSchemes-class . SetOfTimePoints-class . addSchemes . changeDevSettings . checkConstraintsOk . check_scheme_exactNumberObsPerTimePoint . check_scheme_minObsPerTimePoint . check_subject_maxConsecSamples . construct2CompModel . constructSetOfSchemes . doAllSchemeChecks . estimatePopCurve . extractByRank . flagSchemesMeetingConstraints . flattenSetOfSchemes . formatTimePoints . genMVN . get2ComptModelCurve . getAllTimeOptions . getCoeffVariationError . getCombinationsWithMaxNRepetitions . getConstraintsExample . getCorrelationMatrix . getData . getDevRankingSettings . getDosingInfo . getExampleData . getExampleObjective . getExampleParameters . getExamplePkCurve . getExamplePkModel . getExamplePkModelRange . getExampleSetOfSchemes . getExampleSetOfTimePoints . getExampleTimeData . getExampleTimeZones . getIndividualParameters . getMMCurve . getModelFunction . getNSchemes . getNSubjects . getNames . getParameters . getPkData . getPkModel . getPkModelArticle . getPkModels . getRanking . getResultPerScheme . getSetOfSchemes . getSummaryRanks . getTimeChoicePerformance . getTimePoints . getTopNRanking . grapes-ARC-grapes . oneCompartmentOralModel . pkCurveStat . pkOdeModel2Compartments . plotAverageRat . plotMMCurve . plotMMKinetics . plotObject . rankBasedOnDirectory . rankObject . rankObjectWithRange . runMicrosamplingDesignApp . setCoeffVariationError . setCorrelationMatrix . setDosingInfo . setModelToAverageRat . setParameters . setRanking . setTimePoints . subsetOnTimePoints . summary-SetOfSchemes-method . summary .
Some associated R codes: RcppExports.R . aaaGenerics.R . appFunctions.R . constraintFunctions.R . fastRankSchemes.R . internalHelpers.R . objectPkModel.R . objectPkModelParent.R . objectPkModelRange.R . objectSetOfSchemes.R . objectSetOfTimePoints.R . pkFunctions.R . rankScheme.R . rankTimePoints.R . schemeGenerator.R . schemeStatistics.R . timePointGeneration.R . Full microsamplingDesign package functions and examples
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