Package: vpc 1.2.3

Ron Keizer

vpc: Create Visual Predictive Checks

Visual predictive checks are a commonly used diagnostic plot in pharmacometrics, showing how certain statistics (percentiles) for observed data compare to those same statistics for data simulated from a model. The package can generate VPCs for continuous, categorical, censored, and (repeated) time-to-event data.

Authors:Ron Keizer [aut, cre], Bill Denney [aut]

vpc_1.2.3.tar.gz
vpc_1.2.3.zip(r-4.5)vpc_1.2.3.zip(r-4.4)vpc_1.2.3.zip(r-4.3)
vpc_1.2.3.tgz(r-4.4-any)vpc_1.2.3.tgz(r-4.3-any)
vpc_1.2.3.tar.gz(r-4.5-noble)vpc_1.2.3.tar.gz(r-4.4-noble)
vpc_1.2.3.tgz(r-4.4-emscripten)vpc_1.2.3.tgz(r-4.3-emscripten)
vpc.pdf |vpc.html✨
vpc/json (API)
NEWS

# Install 'vpc' in R:

install.packages('vpc', repos = c('https://ronkeizer.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ronkeizer/vpc/issues

Datasets:

rtte_obs_nm - Simulated RTTE data
rtte_sim_nm - Simulated RTTE data
simple_data - A small rich dataset

On CRAN:

23 exports 36 stars 3.71 score 52 dependencies 6 dependents 3 mentions 328 scripts 1.1k downloads

Last updated 3 months agofrom:ec210170e7. Checks:OK: 7. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Sep 11 2024
R-4.5-win	OK	Sep 11 2024
R-4.5-linux	OK	Sep 11 2024
R-4.4-win	OK	Sep 11 2024
R-4.4-mac	OK	Sep 11 2024
R-4.3-win	OK	Sep 11 2024
R-4.3-mac	OK	Sep 11 2024

Exports:add_noise as_vpcdb auto_bin bin_data create_vpc_theme ggplot.vpcdb_categorical ggplot.vpcdb_censored ggplot.vpcdb_continuous ggplot.vpcdb_time_to_event new_vpc_theme plot_vpc plot_vpc_helper quantile_cens read_table_nm replace_list_elements show_default theme_empty theme_plain vpc vpc_cat vpc_cens vpc_tte vpc_vpc

Dependencies:bit bit64 class classInt cli clipr colorspace cpp11 crayon dplyr e1071 fansi farver generics ggplot2 glue gtable hms isoband KernSmooth labeling lattice lifecycle magrittr MASS Matrix mgcv munsell nlme pillar pkgconfig prettyunits progress proxy purrr R6 RColorBrewer readr rlang scales stringi stringr survival tibble tidyr tidyselect tzdb utf8 vctrs viridisLite vroom withr

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
VPC package	vpc-package
Add noise / residual error to data	add_noise
Add sim index number	add_sim_index_number
Adds stratification to data set	add_stratification
Create a vpcdb object, and standardize parameter checking	as_vpcdb
Calculate appropriate bin separators for vpc	auto_bin auto_bin.data.frame auto_bin.numeric
Function to bin data based on a vector of bin separators, e.g. for use in VPC	bin_data
Perform prediction-correction	calc_pred_corr_continuous
Calculate aggregate statistics for simulated and observed VPC data	calc_vpc_continuous
Check whether stratification columns are available	check_stratification_columns_available
Compute Kaplan-Meier statistics	compute_kaplan
Compute KMMC statistics	compute_kmmc
Create new vpc theme	create_vpc_theme
Define bins for many types of data	define_bins define_bins_tte
Define data column defaults for various softwares	define_data_columns
Check and standardize limits of quantification	define_loq
Draw parameters from multivariate distribution	draw_params_mvr
Remove values that are not observed values from data	filter_dv
Prepare VPC data for future calculations by standardizing column names and modifying the input data based on the limits of quantification, stratification, and logarithmic values.	format_vpc_input_data format_vpc_input_data_tte
Create a ggplot for each vpcdb type	ggplot.vpcdb_categorical ggplot.vpcdb_censored ggplot.vpcdb_continuous ggplot.vpcdb_time_to_event
Function copied from ggplot2:::label_variable, with addition of ` Copied here since CRAN does not like use of `:::`.	ggplot2_label_variable
Custom ggplot2 labeller function.	label_vpc_tte
Calculate fraction of observations below lloq / above uloq	loq_frac
Create a customized VPC theme	new_vpc_theme
Simulate PK data from a 1-compartment iv model	pk_iv_1cmt
Simulate PK data from a 1-compartment oral model	pk_oral_1cmt
VPC plotting function	plot_vpc
Core prediction correction function	pred_correction_core
Calculate quantiles respecting the censored data	quantile_cens
NONMEM output table import function	read_table_nm
Read in VPC data	read_vpc
Replace list elements by name	replace_list_elements
Simulated RTTE data (1x)	rtte_obs_nm
Simulated RTTE data (100x)	rtte_sim_nm
Defaults for show argument with various endpoint types	show_default
A small rich dataset	simple_data
Confirm that a column is in the data, and rename data to prepare that column for later use.	standardize_column
Empty ggplot2 theme	theme_empty
A nicer default theme for ggplot2	theme_plain
Lower to full triangle	triangle_to_full
VPC function	vpc vpc.default vpc_vpc
VPC function for categorical	vpc_cat
VPC function for left- or right-censored data (e.g. BLOQ data)	vpc_cens
A collection of internal ggplot helpers for VPC plotting	facet_continuous facet_tte geom_bin_sep geom_hline_loq geom_obs_cens_dat_tte geom_obs_ci_continuous geom_obs_ci_tte geom_obs_dv_continuous geom_obs_km geom_obs_median_continuous geom_sim_km geom_sim_median_ci_continuous geom_sim_median_continuous geom_sim_median_tte geom_sim_pi_as_area_continuous geom_sim_pi_as_area_tte geom_sim_pi_ci_continuous geom_sim_pi_continuous guides_stratify_color scale_x_log10_vpc scale_y_log10_vpc vpc_ggplot
VPC function for time-to-event (survival) data	vpc_tte