simulateBealModelMixedEffects: simulate data from Beal model with fixed and random effects

Description Usage Arguments Details Value Author(s) See Also Examples

View source: R/simulateBealModelMixedEffects.R

Description

function to generate data from a Beal model with fixed effects

Usage

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simulateBealModelMixedEffects(
  numSubjects,
  clearance,
  volumeOfDistribution,
  dose,
  varCompClearance,
  varCompVolumeOfDistribution,
  timePoints
)

Arguments

numSubjects

scalar, number of subject which should be generated

clearance

scalar, clearance

volumeOfDistribution

scalar, volume of distribution

dose

scalar, dose

varCompClearance

scalar, standard error of the normal distribution generating clearance

varCompVolumeOfDistribution

scalar, standard error of the normal distribution generating volume of distribution

timePoints

vector of time points

Details

The model used to generate data at time t is as follows

y(t)=C(t)\exp(e(t)),

where C(t), the PK-model, is defined as follows:

C(t) = \frac{\mathrm{dose}}{V_d} \exp{(CL.t)},

with V_d the volume of distribution and CL as clearance. The error model is consdiered as e(t) \sim N(0, h(t)), with:

h(t) = 0.03 + 0.165 \frac{C(t)^{-1}}{C(1.5)^{-1} + C(t)^{-1}}.

For the mixed effects model, CL=\widetilde{CL} \exp{(η_1)}, and V_d=\widetilde{V_d} \exp{(η_2)}, where η_1 \sim N(0, w_1^2) and η_1 \sim N(0, w_2^2). Note that w_1 and w_2 are specified by varCompClearance, and varCompVolumeOfDistribution in the arguments, respectively.

Value

generated sample with numSubjects as the number of rows and length of timePoints as the number of columns

Author(s)

Vahid Nassiri, Helen Yvette Barnett

See Also

Beal S. L., Ways to fit a PK model with some data below the quantification limit, Journal of Pharmacokinetics and Pharmacodynamics, 2001;28(5):481–504.

Examples

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set.seed(111)
simulateBealModelMixedEffects(10, 0.693,
+ 		1, 1, 0.2,0.2, seq(0.5,3,0.5))

BLOQ documentation built on July 1, 2020, 11:37 p.m.