vpc: vpc_cens – R documentation

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vpc_cens

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,
  plot = FALSE,
  xlab = "Time",
  ylab = "Probability of <LOQ",
  title = NULL,
  smooth = TRUE,
  vpc_theme = NULL,
  facet = "wrap",
  labeller = NULL,
  vpcdb = FALSE,
  verbose = FALSE
)

Arguments

`sim`	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
`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", or a numeric vector specifying the bin separators.
`n_bins`	number of bins
`bin_mid`	either "mean" for the mean of all timepoints (default) or "middle" to use the average of the bin boundaries.
`obs_cols`	observation dataset column names (list elements: "dv", "idv", "id", "pred")
`sim_cols`	simulation dataset column names (list elements: "dv", "idv", "id", "pred")
`software`	name of software platform using (e.g. nonmem, phoenix)
`show`	what to show in VPC (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.
`plot`	Boolean indicating whether to plot the ggplot2 object after creation. Default is FALSE.
`xlab`	ylab as numeric vector of size 2
`ylab`	ylab as numeric vector of size 2
`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, and a ggplot2 object

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)

vpc

Create Visual Predictive Checks

v1.2.2

MIT + file LICENSE

Authors

Ron Keizer <ronkeizer@gmail.com>

Initial release

2021-01-11