Package: multiverse
Version: 0.6.1
Date: 2022-7-2
Title: 'Explorable Multiverse' Data Analysis and Reports
Authors@R: c(
        person("Abhraneel", "Sarma", role = c("aut", "cre"), email = "abhraneel@u.northwestern.edu"),
        person("Matthew", "Kay", role = "aut", email = "mjskay@northwestern.edu"),
        person("Michael", "Moon", role = "ctb", email = "moon@utstat.toronto.edu"),
        person("Mark", "Miller", role = "ctb", email = "725mrm@gmail.com"),
        person("Alex", "Kale", role = "ctb", email = "kalea@uw.edu"),
        person("Nathan", "Taback", role = "ctb", email = "nathan.taback@utoronto.ca"),
        person("Fanny", "Chevalier", role = "ctb", email = "fanny@dgp.toronto.edu"),
        person("Jessica", "Hullman", role = "ctb", email = "jessica.hullman@gmail.com"),
        person("Pierre", "Dragicevic", role = "ctb", email = "pierre.dragicevic@inria.fr"),
        person("Yvonne", "Jansen", role = "ctb", email = "yvonne.jansen@sorbonne-universite.fr")
    )
Maintainer: Abhraneel Sarma <abhraneel@u.northwestern.edu>
Description: Implement 'multiverse' style analyses (Steegen S., Tuerlinckx F, Gelman A., Vanpaemal, W., 2016)
    <doi:10.1177/1745691616658637>, (Dragicevic P., Jansen Y., Sarma A., Kay M., Chevalier F., 2019) <doi:10.1145/3290605.3300295> 
    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.
License: GPL (>= 3)
Encoding: UTF-8
RoxygenNote: 7.2.0
Depends: R (>= 3.5.0), knitr (>= 1.3.2)
Imports: dplyr (>= 0.8.1), purrr (>= 0.3.2), rlang (>= 0.4.0), R6,
        methods, tidyr (>= 1.0.0), tibble, magrittr, tidyselect,
        formatR, collections, evaluate, rstudioapi, berryFunctions,
        future.apply
Suggests: ggplot2 (>= 3.0.0), testthat (>= 2.1.0), highr, rmarkdown,
        covr, broom, boot, gganimate, gifski, forcats, stringr,
        cowplot, tidybayes, png, stringi, modelr, styler, future
VignetteBuilder: knitr
Language: en-US
BugReports: https://github.com/MUCollective/multiverse/issues/new
URL: https://mucollective.github.io/multiverse/,
        https://github.com/mucollective/multiverse/
NeedsCompilation: no
Packaged: 2022-07-02 20:15:56 UTC; abhraneelsarma
Author: Abhraneel Sarma [aut, cre],
  Matthew Kay [aut],
  Michael Moon [ctb],
  Mark Miller [ctb],
  Alex Kale [ctb],
  Nathan Taback [ctb],
  Fanny Chevalier [ctb],
  Jessica Hullman [ctb],
  Pierre Dragicevic [ctb],
  Yvonne Jansen [ctb]
Repository: CRAN
Date/Publication: 2022-07-04 13:20:02 UTC
Built: R 4.2.3; ; 2024-04-24 02:39:21 UTC; windows
