Validates NONMEM estimation model with an mrgsolve simulation model

This function uses the estimates from a NONMEM run and compares this with the results of a simulation run. This function is inspired by a blog post from mrgsolve and mainly looks at the differences in population predictions

Usage

model_validation(
  nmtable,
  simmodel,
  rounding = 4,
  comppred = "CP",
  out = "validate/result.tex",
  ...
)

Arguments

nmtable: either a character with a file or a data frame including the NONMEM table output
simmodel: character with the file including the mrgsolve model
rounding: numeric with the rounding applied for comparing
comppred: character with the variable in mrgsolve model that should be compared with PRED variable in NONMEM
out: character with the name of the output to create
...: additional arguments passed through to mrgsim function

Value

a file with a PDF report is returned

Details

For a correct comparison, the nmtable should include all variables related to dosing (e.g. AMT/CMT/EVID). The simulation model should be available as a separate file that can be read in using mrgsolve::mread. To use the function, the packages R3port, ggplot2, mrgsolve and dplyr should be installed. Be aware that no variables are renamed in $TABLE in the NONMEM control stream (e.g. AMT2=AMT). This can have unexpected results when comparing.

Author

Richard Hooijmaijers

Examples


if (FALSE) { # \dontrun{
  res  <- model_validation(system.file("testfiles/compareParfile",package="amp.sim"),
                           system.file("testfiles/compareModel.cpp",package="amp.sim"),
                           out=NULL)
} # }