'Explorable Multiverse' Data Analysis and Reports

Implement 'multiverse' style analyses (Steegen S., Tuerlinckx F, Gelman A., Vanpaemal, W., 2016) , (Dragicevic P., Jansen Y., Sarma A., Kay M., Chevalier F., 2019) 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) 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.


Reference manual

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0.5.0 by Abhraneel Sarma, 8 months ago

https://mucollective.github.io/multiverse/, https://github.com/mucollective/multiverse/

Report a bug at https://github.com/MUCollective/multiverse/issues/new

Browse source code at https://github.com/cran/multiverse

Authors: Abhraneel Sarma [aut, cre] , Michael Moon [aut] , Matthew Kay [aut] , Alex Kale [ctb] , Nathan Taback [ctb] , Fanny Chevalier [ctb] , Jessica Hullman [ctb] , Pierre Dragicevic [ctb] , Yvonne Jansen [ctb]

Documentation:   PDF Manual  

GPL (>= 3) license

Imports dplyr, purrr, rlang, R6, methods, tidyr, tibble, magrittr, tidyselect, formatR, collections, evaluate, rstudioapi, berryFunctions

Depends on knitr

Suggests ggplot2, testthat, highr, lubridate, rmarkdown, covr, broom, boot, gganimate, gifski, forcats, stringr, cowplot, tidybayes, png, stringi, modelr, styler

See at CRAN