dfpk (version 2.0.0)

scenarios: Generate new data from a scenarios.

Description

This function can be used to generate/simulate new data from several scenarios.

Usage

scenarios(param_pk, omega2, omega_a, sigma2, preal, limit_tox, time_sampling, N)

Arguments

param_pk

Subject's pharmacokinetic's (PK) parameters.

omega2

The standard deviation of the log-normal distribution that the pharmacokinetic's (PK) parameters, clearance(CL) and volume(V), come from; it's equal to 70% or 30% in different scenarios.

omega_a

The standard deviation of the log-normal distribution which the sensitivity parameter $\alpha$ comes from.

sigma2

The additive or proportional error.

preal

The true probabilities of toxicity.

limit_tox

The threshold on toxicity.

time_sampling

Time sampling.

N

The total number of enrolled patients.

References

Ursino, M., et al, (2016) Dose-finding methods using pharmacokinetics in small populations (under review).

See Also

nsim

Examples

limit_tox <- 10.96                  
N <- 42                               
param_pk <- c(2,10,100)       # PK parameters ka,CL,V
omega2 <- 0.7                 # Inter-individual
omega_a <- 0                    
preal <- c(0.001,.05,0.1,.2,0.35,0.45) 
time_sampling <- seq(0,24,length.out=48)    
sigma2 <- c(rep(0.2,length(time_sampling)),rep(0.2,length(time_sampling)))           
# sigma2: Additive or proportional error

gen.scen <- scenarios(param_pk,omega2,omega_a,sigma2,preal,limit_tox,time_sampling, N) 
gen.scen