'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.


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("multiverse")

0.5.0 by Abhraneel Sarma, 20 days 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