getIndividualParameters: sample subject specific parameters to input in...

In microsamplingDesign: Finding Optimal Microsampling Designs for Non-Compartmental Pharmacokinetic Analysis

Description

sample subject specific parameters to input in pharmacodynamic model paramaters are sample from a log-normal distribution

Usage

getIndividualParameters(meanParam, coeffVariation, nSubjects,
  corrMatrix = NULL)

Arguments

meanParam	numeric vector containing mean information of a set of parameters
coeffVariation	coefficient of variantion to inform the variance of the subject
nSubjects	the number of subjects which should be sampled
corrMatrix	optional correlation matrix when not specified parameters are assumed independent

Value

a matrix with rows subject and columns parameters

Examples

  parameters              <-  c( 1 , 0.1 , 10 , 3 )
  names( parameters )     <-  c( "Ka", "Ke" , "volume" , "dose" ) 
  coeffVariation          <-  c( 0.05 , 0.05 , 0.05, 0 )
  names(coeffVariation)   <-  names( parameters )
  nSubjects               <-  9

  # example correlation matrix 
  corrMatrix              <-  matrix(0.2 , nrow = 4 , ncol = 4) +
     diag( rep( 0.8 , 4 ) ) # correlation on the the log scale
  
  # assuming independence between parameters
  getIndividualParameters( parameters , coeffVariation ,  nSubjects = 9 )
  
  # assuming correlations between parameters 
  getIndividualParameters( parameters , coeffVariation ,  nSubjects = 9 , corrMatrix)
  getIndividualParameters( meanParam = parameters , coeffVariation ,  nSubjects = 3 , corrMatrix)

microsamplingDesign documentation built on Oct. 13, 2021, 5:10 p.m.