Package: vachette 1.0.0

James Craig

vachette: A Method for Visualization of Pharmacometric Models

A method to visualize pharmacometric analyses which are impacted by covariate effects. Variability-aligned covariate harmonized-effects and time-transformation equivalent ('vachette') facilitates intuitive overlays of data and model predictions, allowing for comprehensive comparison without dilution effects. 'vachette' improves upon previous methods Lommerse et al. (2021) <doi:10.1002/psp4.12679>, enabling its application to all pharmacometric models and enhancing Visual Predictive Checks (VPC) by integrating data into cohesive plots that can highlight model misspecification.

Authors:Jos Lommerse [aut], Anna Largajolli [aut], James Craig [aut, cre], Nele Mueller-Plock [ctb], Jeff Sachs [ctb], Amy Cheung [ctb], Certara USA, Inc. [cph, fnd]

vachette_1.0.0.tar.gz
vachette_1.0.0.zip(r-4.7)vachette_1.0.0.zip(r-4.6)vachette_1.0.0.zip(r-4.5)
vachette_1.0.0.tgz(r-4.6-any)vachette_1.0.0.tgz(r-4.5-any)
vachette_1.0.0.tar.gz(r-4.7-any)vachette_1.0.0.tar.gz(r-4.6-any)
vachette_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
vachette/json (API)

# Install 'vachette' in R:

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

Bug tracker:https://github.com/certara/vachette/issues

On CRAN:

3.65 score 1 stars 8 scripts 170 downloads 15 exports 77 dependencies

Last updated from:e5f593cf32. Checks:7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	NOTE	162
source / vignettes	OK	252
linux-release-x86_64	NOTE	180
macos-release-arm64	NOTE	134
macos-oldrel-arm64	NOTE	112
windows-devel	NOTE	147
windows-release	NOTE	133
windows-oldrel	NOTE	126
wasm-release	OK	138

Exports:apply_transformations p.add.distances p.obs.cov p.obs.excluded p.obs.ref.query p.prop.distances p.scaled.observation.curves p.scaled.observation.curves.by.id p.scaled.typical.curves p.scaled.typical.curves.landmarks p.scaled.typical.full.curves.landmarks p.scaling.factor p.vachette p.vachette.arrow vachette_data

Dependencies:backports base64enc bslib cachem checkmate cli cluster codetools colorspace cpp11 crayon data.table digest dplyr evaluate farver fastmap fontawesome foreach foreign Formula fs generics ggplot2 glue gridExtra gtable highr Hmisc hms htmlTable htmltools htmlwidgets isoband iterators jquerylib jsonlite knitr labeling lifecycle magrittr mathjaxr memoise mime minpack.lm nnet pillar pkgconfig prettyunits progress prospectr purrr R6 rappdirs RColorBrewer Rcpp RcppArmadillo rlang rmarkdown rpart rstudioapi S7 sass scales splus2R stringi stringr tibble tidyr tidyselect tinytex utf8 vctrs viridisLite withr xfun yaml

Help page	Topics
Apply vachette transformations	apply_transformations apply_transformations.vachette_data
Plot Distances Before and After 'vachette' Transformation Assuming Additive Error Model	p.add.distances
Plot Observations and Typical Curves Faceted by Covariate	p.obs.cov
Plot Excluded Observations with Reasons for Exclusion	p.obs.excluded
Plot Observations and Typical Curves for Query and Reference Data	p.obs.ref.query
Plot Distances Before and After 'vachette' Transformation Assuming Proportional Error Model	p.prop.distances
Plot 'vachette' Transformed Observation Curves	p.scaled.observation.curves
Plot 'vachette' Transformed Observation Curves by Individual	p.scaled.observation.curves.by.id
Plot 'vachette' Transformed Typical Curves	p.scaled.typical.curves
Plot 'vachette' Transformed Typical Curves with Landmarks	p.scaled.typical.curves.landmarks
Plot Full 'vachette' Transformed Typical Curves with Landmarks	p.scaled.typical.full.curves.landmarks
Plot Scaling Factors for Typical Curves	p.scaling.factor
Main Vachette Plot	p.vachette
Plot Observations and 'vachette' Transformed Observations with Connecting Arrows	p.vachette.arrow
Print 'vachette_data'	print.vachette_data
Summarise 'vachette_data'	summary.vachette_data
Initialize vachette object with required data	vachette_data

Package: vachette 1.0.0

vachette: A Method for Visualization of Pharmacometric Models

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