This repository contains the data and code for our paper:

Authors, (YYYY). Title of your paper goes here. Name of journal/book https://doi.org/xxx/xxx

Our pre-print is online here:

Authors, (YYYY). Title of your paper goes here. Name of journal/book, Accessed 12 Aug 2022. Online at https://doi.org/xxx/xxx

Please cite this compendium as:

Authors, (2022). Compendium of R code and data for Title of your paper goes here. Accessed 12 Aug 2022. Online at https://doi.org/xxx/xxx

The analysis directory contains:

• 📁 paper: R Markdown source document for manuscript. Includes code to reproduce the figures and tables generated by the analysis. It also has a rendered version, paper.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
• 📁 supplementary-materials: Supplementary materials including notes and other documents prepared and collected during the analysis.

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). - finally, open analysis/paper/paper.Rmd and knit to produce the paper.docx, or run rmarkdown::render("analysis/paper/paper.Rmd") in the R console

Text and figures : CC-BY-4.0

Code : See the DESCRIPTION file

Data : CC-0 attribution requested in reuse

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.