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: 0.0.5
Depends: R (≥ 3.1.0)
Imports: colourpicker, dplyr, egg, ggplot2, ggstance, ggridges, markdown, shiny, shinyjs, stats, tidyr, utils
Suggests: MASS, knitr, rmarkdown, mrgsolve, ggrepel, table1, patchwork, bayestestR, plotly, scales, Rcpp
Published: 2020-02-06
Author: Samer Mouksassi ORCID iD [aut, cre], Dean Attali [ctb]
Maintainer: Samer Mouksassi <samermouksassi at gmail.com>
BugReports: https://github.com/smouksassi/interactiveforestplot/issues
License: MIT + file LICENSE
URL: https://github.com/smouksassi/interactiveforestplot
NeedsCompilation: no
SystemRequirements: pandoc with https support
Materials: README NEWS
CRAN checks: coveffectsplot results

Downloads:

Reference manual: coveffectsplot.pdf
Vignettes: Exposure_Response_Example
PKPD_Example
PK_Example
Introduction to coveffectsplot
Package source: coveffectsplot_0.0.5.tar.gz
Windows binaries: r-devel: coveffectsplot_0.0.5.zip, r-devel-gcc8: coveffectsplot_0.0.5.zip, r-release: coveffectsplot_0.0.5.zip, r-oldrel: coveffectsplot_0.0.5.zip
OS X binaries: r-release: coveffectsplot_0.0.5.tgz, r-oldrel: coveffectsplot_0.0.5.tgz
Old sources: coveffectsplot archive

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