r-multiverse 0.6.2
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.2.1 r-styler@1.10.3 r-rstudioapi@0.17.1 r-rlang@1.1.6 r-readr@2.1.5 r-r6@2.6.1 r-purrr@1.0.4 r-magrittr@2.0.3 r-knitr@1.50 r-jsonlite@2.0.0 r-furrr@0.3.1 r-formatr@1.14 r-evaluate@1.0.3 r-dplyr@1.1.4 r-distributional@0.5.0 r-collections@0.3.8 r-berryfunctions@1.22.13
Channel: guix-cran
Home page: https://mucollective.github.io/multiverse/
Licenses: GPL 3+
Synopsis: Create 'multiverse analysis' in R
Description:
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.
Total results: 1