The ManyEcoEvo package provides a suite of functions for:
- Summarising, analysing and visualising the ManyEcoEvo dataset from Gould et al.1
 - Tidying and cleaning many-analyst style data for further analysis
 - Reproducing the analysis in Gould et al. using your own many-analyst style data
 
Note that the manuscript source-code for Gould et al. is located in a separate repository at https://github.com/egouldo/ManyAnalysts, which can be viewed at https://egouldo.github.io/ManyAnalysts/.
Installation
ManyEcoEvo:: can be installed using devtools:: from GitHub with:
devtools::install_github("egouldo/ManyEcoEvo")Regenerating the ManyEcoEvo dataset
The data processing and analysis can be freely reproduced with the help of the targets:: package. Please see the documentation at https://docs.ropensci.org/targets/ for further detail.
Should you wish to completely reproduce the dataset generation and analysis in Gould et al., complete the following steps:
- Clone or download https://github.com/egouldo/this repository
 - Run 
renv::restore()to load the packages used in the analysis pipeline locally on your machine (seerenv::for details) - Run 
targets::tar_destroy()to remove any record and caches of existing targets - Run 
targets::tar_make()in your console, depending on the power of your machine, the analysis pipeline will take between 2 and 7 minutes to execute (plus or minus some!) - You can view a table of all targets in the pipeline by running 
targets::tar_meta() - To interact with objects or ‘targets’ within the analysis pipeline, call 
targest::tar_load()ortargets::tar_read(): 
targets::tar_read("ManyEcoEvo")# A tibble: 2 × 4
  dataset    data                diversity_data      estimate_type
  <chr>      <list>              <named list>        <chr>        
1 blue tit   <tibble [174 × 38]> <tibble [174 × 54]> Zr           
2 eucalyptus <tibble [128 × 38]> <tibble [128 × 61]> Zr           The script that generates datasets used in the ManyEcoEvo:: package is located in ManyEcoEvo/data-raw/tar_make.R.
Contributing
This package is released with a Contributor Code of Conduct.
Citation
To cite package ‘ManyEcoEvo’ in publications use:
  Gould E, Fraser H, Nakagawa S, Parker T (2023). _ManyEcoEvo: Meta-analyse
  data from 'Many-Analysts' style studies_. R package version 1.0.0,
  <https://github.com/egouldo/ManyEcoEvo>.
A BibTeX entry for LaTeX users is
  @Manual{,
    title = {ManyEcoEvo: Meta-analyse data from 'Many-Analysts' style studies},
    author = {Elliot Gould and Hannah S. Fraser and Shinichi Nakagawa and Timothy H. Parker},
    year = {2023},
    note = {R package version 1.0.0},
    url = {https://github.com/egouldo/ManyEcoEvo},
  }