Raue, Bioinformatics 31(21), 2015↩︎
Kaschek, dMod, 2016 (https://cran.r-project.org/package=dMod)↩︎
Creates an IQReventTable based on IQR dosing and individual parameters
create_IQReventTable.RdSimulations with sim_IQRmodel of populations are faster if an IQReventTable object is provided, defining the individual dosing scenarios and parameters. To simplify the construction of an IQReventTable object, this function here can be used. The same IQRdosing object will be applied to all subjects or for each subject a IQRdosing in a list. Individual subjects parameters are provided as a data.frame with an ID column containing a numerical subject identifier.
create_IQReventTable(
dosing,
indivData,
regression = NULL,
abs0inputs = NULL,
abs0Tk0param = NULL
)Arguments
- dosing
IQRdosing object or list of doing objects for each individual in indivData
- indivData
data.frame with individual parameters (requires ID column)
- regression
character vector with regression names. If NULL (default) all columns of indivData but "ID" will be used.
- abs0inputs
numeric vector with numbers of inputs (ADM) that are of type ABSORPTION0. If this argument is set also abs0Tk0param needs to be defined
- abs0Tk0param
character vector with names of regression parameters that should be used as 0-order infusion time (by updating TINF). The regression parameters for these values are kept in the event table. Ordering has to be as in abs0inputs
See also
Other Simulation:
IQRdosing(),
IQReventTable(),
create_IQReventData(),
extract_IQRdosing(),
is_IQRdosing(),
is_IQReventTable(),
is_IQRsimresMulti(),
is_IQRsimres(),
plot.IQRsimresMulti(),
plot.IQRsimres(),
print.IQRdosing(),
print.IQReventTable(),
print.IQRsimresMulti(),
print.IQRsimres(),
rbind_IQRdosing(),
sim_IQRmodel()