This repository contains the data and code to generate this short analysis
The analysis directory contains:
- 📁 report: R Markdown source document
for manuscript. Includes code to reproduce the figures and tables
generated by the analysis. It also has a rendered version,
report.docx
, suitable for reading (the code is replaced by figures and tables in this file) - 📁 data: Data used in the analysis.
- 📁 figures: Plots and other illustrations
This research compendium has been developed using the statistical programming language R. To work with the compendium, you will need installed on your computer the R software itself and optionally RStudio Desktop.
You can download the compendium as a zip from from this URL: master.zip. After unzipping:
- open the
.Rproj
file in RStudio - run
devtools::install()
to ensure you have the packages this analysis depends on (also listed in the DESCRIPTION file). - ensure that packages are at the correct versions with
renv::restore()
. - finally, open
analysis/report/report.Rmd
and knit to produce thereport.docx
, or runrmarkdown::render("analysis/report/report.Rmd", params = list(gather_raw_data = FALSE, parallel_ = TRUE, generate_model_fits = FALSE))
in the R console
Code : See the DESCRIPTION file
We welcome contributions from everyone. Before you get started, please see our contributor guidelines. Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.