
Execute a visual predictive check (VPC) simulation using mrgsolve
Source: R/df_mrgsim_replicate.R
df_mrgsim_replicate.Rddf_mrgsim_replicate() is a wrapper function for mrgsolve::mrgsim_df()
that returns a data.frame containing replicates iterations of data
Arguments
- data
Input dataset. Must contain required variables for
mrgsim_df()other than those handled by other arguments.- model
mrgsolvemodel object.- replicates
Number of replicates. Either an integer, or something coercible to an integer.
- dv_var
Character name of the DV variable in
data.- time_vars
Names of actual and nominal time variables. Must be named character vector. Defaults is: c(
TIME="TIME",NTIME="NTIME").- output_vars
Names of model outputs from
model. Must be named character vector. Defaults is: c(PRED="PRED",IPRED="IPRED",DV="DV").- num_vars
Numeric variables in
dataor simulation output to recover. Must be a character vector of variable names from the simulation output tocarry_outand return in output. Defaults are"CMT","EVID","MDV","NTIME".- char_vars
Character variables in
dataor simulation output to recover. Must be a character vector of variable names from the simulation output torecoverand return in output.- irep_name
Name of replicate variable in
data. Must be a string. Default is"SIM".- seed
Random seed. Default is
123456789.- ...
Additional arguments passed to
mrgsolve::mrgsim_df().
Value
A data.frame with data x replicates rows (unless obsonly=TRUE is passed to mrgsolve::mrgsim_df())
and the output variables in output_vars, num_vars, and char_vars.
Examples
model <- model_mread_load(model = "model")
#> Loading model from cache.
simout <- df_mrgsim_replicate(data = data_sad, model = model, replicates = 100,
dv_var = "ODV",
num_vars = c("CMT", "LLOQ", "EVID", "MDV", "WTBL", "FOOD"),
char_vars = c("USUBJID", "PART"),
irep_name = "SIM")