# Create a PopED database for an IQRmodel

Create a PopED database for an IQRmodel

IQRpopEDdb(model, design, modelSpec, transform_pop = FALSE, ...)

## Arguments

model IQRmodel object list to define the design, can contain elements time ( observation time points), dosing (the dosing scheme), groupsize (number of subjects per group). See details and example. list to define model specification. See example. See IQRnlmeEst for a full description of the list structure. Define the reference frame for the population parameters. If TRUE, the parameters are transformed according to the model specification and standard errors are reported on the transformed scale. If FALSE, standard error as reported on the original, untransformed scale. Arguments for create.poped.database

## Value

A PopED database object, see create.poped.database.

## Details

The IQRpopEDdb function uses the model, design and model specification input to internally generate model prediction functions, residual error functions and parameterization functions as being required by create.poped.database. Subsequently, it calls create.poped.database() with the appropriate arguments. Additional arguments can be passed using the ... argument.

The design argument defines the experimental design by a list of

• observation time points,

• dosing scheme,

• group size.

The typical design definition looks like this:

 design <- list( time = list( group1 = list( OUTPUT1 = c(1, 2, 5, 10), OUTPUT2 = c(1, 5, 20) ), group2 = list( OUTPUT1 = c(1, 2, 5, 10), OUTPUT2 = c(1, 5, 20) ) ), dosing = list( group1 = IQRdosing( TIME = 0, ADM = 1, AMT = 40, TINF = 0 ), group2 = . IQRdosing( TIME = 0, ADM = 1, AMT = 40, TINF = 0 )), groupsize = list( group1 = 12, group2 = 3 ) ) 

Groups names do not have to follow the scheme "groupx", but can be arbitrary names.

The element time is defined per group and per model output. Vectors of time points are expected. They can have different length. If the observation time points are the same for all groups, it is sufficient to define them for exactly one group.

The element dosing is defined per group. See IQRdosing for the correct specification of a dosing scheme. The resulting dosing data frames for each group must have equal dimensions. Sometimes this must be enforced by introducing zero amounts by hand. If the dosing is the same for all groups, it is sufficient to define dosing for exactly one group.

The element groupsize defines the number of subjects in each group. The names found in the argument groupsize define the available groups. They are used if time or dosing have been defined for one group only to duplicate the element for each available group.

NOTE ABOUT COVARIATES By default, the AMT columns of the dosings are added as covariates such that popED can optimize the amounts. Other covariates are not yet implemented and have to be specified manually via ...

PopED functions: model_prediction, plot_model_prediction, evaluate_design

Other Optimal Experiment Design: evaluate_IQRpopEDdb(), sim_IQRpopEDdb()