
Plot a visual predictive check (VPC) with exact time bins
Source:R/plot_vpc_exactbins.R
plot_vpc_exactbins.Rd
plot_vpc_exactbins()
is a wrapper function for vpc::vpc()
that returns a ggplot2
object.
Usage
plot_vpc_exactbins(
sim,
pcvpc = FALSE,
time_vars = c(TIME = "TIME", NTIME = "NTIME"),
output_vars = c(PRED = "PRED", IPRED = "IPRED", SIMDV = "SIMDV", OBSDV = "OBSDV"),
loq = NULL,
strat_var = NULL,
irep_name = "SIM",
min_bin_count = 1,
show_rep = TRUE,
lower_bound = 0,
shown = NULL,
theme = NULL,
timeu = "hours",
n_breaks = 8,
...
)
Arguments
- sim
Input dataset. Must contain the following variables:
"ID"
,"TIME"
- pcvpc
logical for prediction correction. Default is
FALSE
.- 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"
.- loq
Numeric value of the lower limit of quantification (LLOQ) for the assay. Passed to
lloq
argument ofvpc::vpc()
. Specifying this argument implies thatOBSDV
is missing insim
where < LLOQ.- strat_var
Character string of stratification variable passed to
stratify
argument ofvpc::vpc()
. Currently, only a single stratifying variable is supported.- irep_name
Name of replicate variable in
data
. Must be a string. Default is"SIM"
.- min_bin_count
Minimum number of quantifiable observations in exact bin for inclusion in binned plot layers. This argument drops small bins from summary statistic calculation but retains these observations in the observed data points.
- show_rep
Display number of replicates as a plot caption. Default is
TRUE
.- lower_bound
Lower bound of the dependent variable for prediction correction. Default is
0
.- shown
Named list of logicals specifying which layers to include on the plot. Passed to
show
argument ofvpc::vpc()
.Defaults are:
Observed points:
obs_dv
= TRUE.Observed quantiles:
obs_ci
= TRUESimulated inter-quantile range:
pi
= FALSESimulated inter-quantile area:
pi_as_area
= FALSESimulated Quantile CI:
pi_ci
= TRUEObserved Median:
obs_median
= TRUESimulated Median:
sim_median
= FALSESimulated Median CI:
sim_median_ci
= TRUE
- theme
Named list of aesthetic parameters for the plot.Passed to
vpc_theme
arumgent ofvpc::vpc()
. Defaults can be obtained by runningvpc::new_vpc_theme()
with no arguments.- timeu
Character string specifying units for the time variable. Passed to
breaks_time
and assigned to default x-axis label. Options include:"hours" (default)
"days"
"weeks"
"months"
- n_breaks
Number of breaks requested for x-axis. Default is 5.
- ...
Other arguments passed to
vpc::vpc()
.
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", "EVID", "MDV", "NTIME", "LLOQ", "WTBL", "FOOD"),
char_vars = c("USUBJID", "PART"),
irep_name = "SIM")
vpc_plot <- plot_vpc_exactbins(
sim = simout,
pcvpc = TRUE,
pi = c(0.05, 0.95),
ci = c(0.05, 0.95),
loq = 1)
#> Joining with `by = join_by(NTIME, CMT)`
#> Joining with `by = join_by(NTIME, CMT)`
#> Prediction-correction cannot be used together with censored data (<LLOQ or >ULOQ). VPC plot will be shown for non-censored data only!