{ceplotr}: Model agnostic plotting for cost effectiveness analysis

This package was outlined ahead of the HE Hackathon 2019 @Imperial. After a group discussion it was not continued in favour of aiming to improve documentation + testing for BCEA

This package aims to:

• Provide standarised modular plotting functions for cost effectiveness analysis.
• Support a single data format which is model and application agnostic.
• Provide data transformation tooling to support cost effectiveness analysis.
• Support converting model simulations, costs, etc. into this standard format.
• Provide detailed documentation of all functionality.
• Support interactive use via an interface.
• Be modular, user modfiable and extendable.
• Be fully tested, reliable and easy to use.

For help getting started see the Getting Started vignette.

Installation

Install the CRAN version (when released):

install.packages("ceplotr")

Alternatively install the development version from GitHub:

# install.packages("remotes")
remotes::install_github("seabbs/ceplotr")

Documentation

Testing

Quick start

Lets get started quickly by

See Functions for more details of the functions used and for more package functionality.

Shiny dashboard

ceplotr::cd_dashboard()

Contributing

File an issue here if there is a feature that you think is missing from the package, or better yet submit a pull request.

Please note that the ceplotr project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

Citing

If using ceplotr please consider citing the package in the relevant work. Citation information can be generated in R using the following (after installing the package),

citation("ceplotr")
#> 
#> To cite ceplotr in publications use:
#> 
#>   Sam Abbott (2019). ceplotr - -
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Article{,
#>     title = {ceplotr},
#>     author = {Sam Abbott},
#>     journal = {-},
#>     year = {2019},
#>   }

Docker

This package has been developed in docker based on the rocker/tidyverse image, to access the development environment enter the following at the command line (with an active docker daemon running),

docker pull seabbs/ceplotr
docker run -d -p 8787:8787 -e USER=ceplotr -e PASSWORD=ceplotr --name getTBinR seabbs/ceplotr

The rstudio client can be accessed on port 8787 at localhost (or your machines ip). The default username is ceplotr and the default password is ceplotr. Alternatively, access the development environment via binder.