simulateBealModelMixedEffects {BLOQ}

R Documentation

simulate data from Beal model with fixed and random effects

Description

function to generate data from a Beal model with fixed effects

Usage

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{(\eta_1)}, and V_d=\widetilde{V_d} \exp{(\eta_2)}, where \eta_1 \sim N(0, w_1^2) and \eta_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

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

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