Implement 'multiverse' style analyses (Steegen S., Tuerlinckx F, Gelman A., Vanpaemal, W., 2016)
<doi:10.1177/1745691616658637> to show the robustness of statistical inference.
'Multiverse analysis' is a philosophy of statistical reporting where paper authors
report the outcomes of many different statistical analyses in order to show how
fragile or robust their findings are. The 'multiverse' package
(Sarma A., Kale A., Moon M., Taback N., Chevalier F., Hullman J., Kay M., 2021)
<doi:10.31219/osf.io/yfbwm> allows users to concisely and flexibly implement 'multiverse-style'
analysis, which involve declaring alternate ways of performing an analysis step, in R and R Notebooks.
| Version: |
0.6.2 |
| Depends: |
R (≥ 3.5.0), knitr (≥ 1.3.2) |
| Imports: |
dplyr (≥ 0.8.1), purrr (≥ 0.3.4), rlang (≥ 0.4.0), R6, methods, tidyr (≥ 1.0.0), tibble, magrittr, tidyselect, formatR, collections, evaluate, rstudioapi, berryFunctions, furrr, styler, distributional, jsonlite, readr |
| Suggests: |
ggplot2 (≥ 3.0.0), testthat (≥ 3.0.0), highr, rmarkdown, covr, broom, boot, gganimate, gifski, forcats, stringr, cowplot, tidybayes, png, stringi, modelr, future |
| Published: |
2024-10-07 |
| DOI: |
10.32614/CRAN.package.multiverse |
| Author: |
Abhraneel Sarma [aut, cre],
Matthew Kay [aut],
Michael Moon [ctb],
Mark Miller [ctb],
Kyle Hwang [ctb],
Hadley Wickham [ctb],
Alex Kale [ctb],
Nathan Taback [ctb],
Fanny Chevalier [ctb],
Jessica Hullman [ctb],
Pierre Dragicevic [ctb],
Yvonne Jansen [ctb] |
| Maintainer: |
Abhraneel Sarma <abhraneel at u.northwestern.edu> |
| BugReports: |
https://github.com/MUCollective/multiverse/issues/ |
| License: |
GPL (≥ 3) |
| URL: |
https://mucollective.github.io/multiverse/,
https://github.com/mucollective/multiverse/ |
| NeedsCompilation: |
no |
| Language: |
en-US |
| Citation: |
multiverse citation info |
| Materials: |
README NEWS |
| CRAN checks: |
multiverse results |