vpc_cens: VPC function for left- or right-censored data (e.g. BLOQ...

In ronkeizer/vpc: Create Visual Predictive Checks

VPC function for left- or right-censored data (e.g. BLOQ data)

Description

Creates a VPC plot from observed and simulation data for censored data. Function can handle both left- (below lower limit of quantification) and right-censored (above upper limit of quantification) data.

Usage

vpc_cens(
  sim = NULL,
  obs = NULL,
  psn_folder = NULL,
  bins = "jenks",
  n_bins = 8,
  bin_mid = "mean",
  obs_cols = NULL,
  sim_cols = NULL,
  software = "auto",
  show = NULL,
  stratify = NULL,
  stratify_color = NULL,
  ci = c(0.05, 0.95),
  uloq = NULL,
  lloq = NULL,
  xlab = "Time",
  ylab = "Probability of <LOQ",
  title = NULL,
  smooth = TRUE,
  vpc_theme = NULL,
  facet = "wrap",
  labeller = NULL,
  vpcdb = FALSE,
  verbose = FALSE
)

Arguments

sim	this is usually a data.frame with observed data, containing the independent and dependent variable, a column indicating the individual, and possibly covariates. E.g. load in from NONMEM using read_table_nm. However it can also be an object like a nlmixr or xpose object
obs	a data.frame with observed data, containing the independent and dependent variable, a column indicating the individual, and possibly covariates. E.g. load in from NONMEM using read_table_nm
psn_folder	instead of specifying "sim" and "obs", specify a PsN-generated VPC-folder
bins	either "density", "time", or "data", "none", or one of the approaches available in classInterval() such as "jenks" (default) or "pretty", or a numeric vector specifying the bin separators.
n_bins	when using the "auto" binning method, what number of bins to aim for
bin_mid	either "mean" for the mean of all timepoints (default) or "middle" to use the average of the bin boundaries.
obs_cols	list for mapping observation data columns, e.g. 'list(dv = "DV", id = "ID", idv = "TIME", pred="PRED")'
sim_cols	list for mapping simulation data columns, e.g. 'list(dv = "DV", id = "ID", idv = "TIME", pred="PRED")'
software	name of software platform using (e.g. nonmem, phoenix)
show	what to show in VPC (obs_dv, obs_ci, pi, pi_as_area, pi_ci, obs_median, sim_median, sim_median_ci)
stratify	character vector of stratification variables. Only 1 or 2 stratification variables can be supplied.
stratify_color	variable to stratify and color lines for observed data. Only 1 stratification variables can be supplied.
ci	confidence interval to plot. Default is (0.05, 0.95)
uloq	Number or NULL indicating upper limit of quantification. Default is NULL.
lloq	Number or NULL indicating lower limit of quantification. Default is NULL.
xlab	label for x axis
ylab	label for y axis
title	title
smooth	"smooth" the VPC (connect bin midpoints) or show bins as rectangular boxes. Default is TRUE.
vpc_theme	theme to be used in VPC. Expects list of class vpc_theme created with function vpc_theme()
facet	either "wrap", "columns", or "rows"
labeller	ggplot2 labeller function to be passed to underlying ggplot object
vpcdb	boolean whether to return the underlying vpcdb rather than the plot
verbose	show debugging information (TRUE or FALSE)

Value

a list containing calculated VPC information (when vpcdb=TRUE), or a ggplot2 object (default)

See Also

sim_data, vpc, vpc_tte, vpc_cat

Examples

## See vpc.ronkeizer.com for more documentation and examples
library(vpc)

vpc_cens(sim = simple_data$sim, obs = simple_data$obs, lloq = 30)
vpc_cens(sim = simple_data$sim, obs = simple_data$obs, uloq = 120)

ronkeizer/vpc documentation built on May 11, 2023, 11:09 p.m.