simulateBealModelMixedEffects {BLOQ} | R Documentation |
function to generate data from a Beal model with fixed effects
simulateBealModelMixedEffects( numSubjects, clearance, volumeOfDistribution, dose, varCompClearance, varCompVolumeOfDistribution, timePoints )
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 |
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.
generated sample with numSubjects as the number of rows and length of timePoints as the number of columns
Vahid Nassiri, Helen Yvette Barnett
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.
set.seed(111) simulateBealModelMixedEffects(10, 0.693, + 1, 1, 0.2,0.2, seq(0.5,3,0.5))