
Execute a visual predictive check (VPC) simulation using mrgsolve
Source: R/df_mrgsim_replicate.R
df_mrgsim_replicate.Rd
df_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
mrgsolve
model 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 are
"TIME"
and"NTIME"
.- output_vars
Names of model outputs from
model
. Must be named character vector. Defaults are"PRED"
,"IPRED"
, and"DV"
.- num_vars
Numeric variables in
data
or simulation output to recover. Must be a character vector of variable names from the simulation output tocarry_out
and return in output. Defaults are"CMT"
,"EVID"
,"MDV"
,"NTIME"
.- char_vars
Character variables in
data
or simulation output to recover. Must be a character vector of variable names from the simulation output torecover
and 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")