nlme.modeltrail: Model trail / Runrecord for series of nested nlme models

In qPharmetra/qpToolkit: qPharmetra R Tools

Model trail / Runrecord for series of nested nlme models

Description

create a model trial (or runrecord) for a series of nested models. This requires A problem statement as well as a reference model to be added to the nlme object. This is ensure by using qPharmetra's nlme.run instead of nlme.

Usage

## S3 method for class 'modeltrail'
nlme(...)

Arguments

...	nlme object names separated by a comma

Value

data.frame containing the nlme model trail

See Also

nlme.run

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.PD001.nlme = nlme.run(
   model = value ~ base * exp(base.eta) ,
   data = subset(pkpdData,type == "PD" & dose > 0 & value > 0.5),
   fixed = base ~ 1,
   random = base.eta  ~ 1,
   groups = ~ id,
   start = c(base = 1),
   problem = "Baseline Only Model",
   reference = 0
)
fit.PD002.nlme = nlme.run(
   model = value ~ base * exp(base.eta) + tSlope*time,
   data = subset(pkpdData,type == "PD" & dose > 0 & value > 0.5),
   fixed = base + tSlope ~ 1,
   random = base.eta  ~ 1,
   groups = ~ id,
   start = c(base = 1, tSlope = 0.01),
   problem = "Linear Time-Slope Model",
   reference = 1)
fit.PD003.nlme = nlme.run(
   model = value ~ base * exp(base.eta) + tSlope*time + dSlope * dose,
   data = subset(pkpdData,type == "PD" & dose > 0 & value > 0.5),
   fixed = base + tSlope + dSlope ~ 1,
   random = base.eta  ~ 1,
   groups = ~ id,
   start = c(base = 1, tSlope = 0.01, dSlope = 0.01),
   problem = "Linear Time-Slope+Dose-Slope Model",
   reference = 2)
fit.PD004.nlme = nlme.run(
   model = value ~ base + EFF.1comp.1abs(dose, time, cl * exp(cl.eta), v, ka, keo),
   data = subset(pkpdData,type == "PD" & dose > 0 & 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 = 3)
nlme.modeltrail(fit.PD001.nlme,fit.PD002.nlme,fit.PD003.nlme,fit.PD004.nlme)

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