README.qmd

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# Source Code for the ManyEcoEvo Manuscipt <img src="inst/ManyEcoEvoHex.jpg" align="right" width="120"/>

This repository contains the source code for generating the ManyEcoEvo Manuscript *"Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology."*[^1]

The data primary analysis code and pipeline is stored and executed in the R package `ManyEcoEvo::`, located at [https://doi.org/10.5281/zenodo.10046153](https://doi.org/10.5281/zenodo.10046153) or [https://github.com/egouldo/ManyEcoEvo](https://github.com/egouldo/ManyEcoEvo).

# Reproducing the manuscript on your machine

1. Clone or download and unzip this repository
2. Open the `ManyAnalysts.Rproj` file in RStudio
3. Install `renv::` and Run `renv::restore()` to load the packages used in this repository locally on your machine (see  [renv::](https://rstudio.github.io/renv/index.html) for details). Follow the prompts, and if `ManyEcoEvo::` does not install, install it with: `devtools::install_github("egouldo/ManyEcoEvo").
4. In the console, run `quarto::quarto_render()`, output will be created in `_book/index.html`.


# License [![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)

The code in this repository is licensed with the GNU GPL 3 license.

# Contributing

Should you find any mistakes or errors, please lodge a GitHub issue at [https://github.com/egouldo/ManyAnalysts/issues](https://github.com/egouldo/ManyAnalysts/issues). This repository is released with a [Contributor Code of Conduct](https://github.com/egouldo/ManyAnalysts/blob/6a2585fb9225575a97ed87033ad57aa095f23170/CODE_OF_CONDUCT.md) [![Contributor Covenant](https://img.shields.io/badge/Contributor%20Covenant-2.1-4baaaa.svg)](code_of_conduct.md).

[^1]: Gould, E., Fraser, H., Parker, T.
    *et al.* (2023).
    Same data, different analysts: Variation in effect sizes due to analytical decisions in ecology and evolutionary biology \[Preprint\].
    Ecology and Evolutionary Biology.
    https://doi.org/10.32942/X2GG62