coveffectsplot: Produce Forest Plots to Visualize Covariate Effects

Produce forest plots to visualize covariate effects using either the command line or an interactive 'Shiny' application.

Version: 0.0.9.1
Depends: R (≥ 3.6.0), data.table (≥ 1.9.8)
Imports: colourpicker, dplyr, egg, ggplot2 (≥ 3.3.2), markdown, shiny, shinyjs, stats, tidyr, table1, utils
Suggests: clipr, formatR, MASS, knitr, rmarkdown, mrgsolve, ggridges, ggrepel, ggstance, patchwork, bayestestR, plotly, scales, shinyAce, Rcpp, gamlss.dist
Published: 2020-12-10
Author: Samer Mouksassi ORCID iD [aut, cre], Dean Attali [ctb]
Maintainer: Samer Mouksassi <samermouksassi at gmail.com>
BugReports: https://github.com/smouksassi/coveffectsplot/issues
License: MIT + file LICENSE
URL: https://github.com/smouksassi/coveffectsplot
NeedsCompilation: no
SystemRequirements: pandoc with https support
Materials: README NEWS
CRAN checks: coveffectsplot results

Documentation:

Reference manual: coveffectsplot.pdf
Vignettes: Exposure_Response_Example
Introduction to coveffectsplot
PKPD_Example
PK_Example
Pediatric_Cov_Sim

Downloads:

Package source: coveffectsplot_0.0.9.1.tar.gz
Windows binaries: r-devel: coveffectsplot_0.0.9.1.zip, r-release: coveffectsplot_0.0.9.1.zip, r-oldrel: coveffectsplot_0.0.9.1.zip
macOS binaries: r-release (arm64): coveffectsplot_0.0.9.1.tgz, r-release (x86_64): coveffectsplot_0.0.9.1.tgz, r-oldrel: coveffectsplot_0.0.9.1.tgz
Old sources: coveffectsplot archive

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