nlme.vpc: Create VPC output of an nlme object

In qPharmetra/qpToolkit: qPharmetra R Tools

Create VPC output of an nlme object

Description

Creates a VPC object of an nlme object ready for plotting

Usage

## S3 method for class 'vpc'
nlme(
  object,
  nrep = 10,
  covariates,
  fun = smedian.hilow,
  newdata = NULL,
  return.samp = FALSE
)

Arguments

object	an nlme object
nrep	number of samples (defaulting to 10)
covariates	covariates (like time and dose) to be used with the graph
fun	function used to summarize simulated output. Defaults to smedian.hilow from the Hmisc package.
newdata	if supplied allows simulating a VPC for another data set than the model data set. This dataset does need the dependent variable, independent variable, grouping variable, and any other covariate used in the model.
return.samp	if T returns the non-summarized predictions as well

Value

a list with

Examples

library(nlme)
pkpdData = example.pkpdData()
 EFF.1comp.1abs <- function(dose, tob, cl, v, ka, keo)
 {
   # Effect-site concentration for 1-compartment model, 1st-order absorption

   kel = cl / v

   # Define coefficients
   A = 1/(kel-ka) / (keo-ka)
   B = 1/(ka-kel) / (keo-kel)
   C = 1/(ka-keo) / (kel-keo)

   # Return effect-site concentration
   dose*ka*keo/v * (A*exp(-ka*tob) + B*exp(-kel*tob) + C*exp(-keo*tob))
 }
 fit.PD004.nlme = nlme.run(
   model = value ~ base + EFF.1comp.1abs(dose, time, cl * exp(cl.eta), v, ka, keo),
   data = pkpdData[pkpdData$type == "PD" & pkpdData$dose > 0 & pkpdData$value > 0.5, ],
   fixed = base + cl + v + ka + keo ~ 1,
   random = cl.eta ~ 1,
   groups = ~ id,
   start = c(base = 1, cl = 1, v = 10, ka = 1, keo = 0.01),
   problem = "True Model",
   reference = 4)
 summary(fit.PD004.nlme$object)
 nlme.extract(fit.PD004.nlme$object)$table
 vpc.PD004.nlme = nlme.vpc(fit.PD004.nlme$object, nrep = 100)
 nlme.vpcplot(fit.PD004.nlme$object, vpc.PD004.nlme)

qPharmetra/qpToolkit documentation built on May 24, 2023, 8:52 a.m.