DESCRIPTION

Package: dabestr
Type: Package
Title: Data Analysis using Bootstrap-Coupled Estimation
Version: 0.3.0
Authors@R: c(
    person("Joses W.", "Ho",
          email = "joseshowh@gmail.com", role = c("cre", "aut")),
    person("Tayfun", "Tumkaya",
          role = c("aut"))
          )
Maintainer: Joses W. Ho <joseshowh@gmail.com>
Description: Data Analysis using Bootstrap-Coupled ESTimation.
    Estimation statistics is a simple framework that avoids the pitfalls of
    significance testing. It uses familiar statistical concepts: means,
    mean differences, and error bars. More importantly, it focuses on the
    effect size of one's experiment/intervention, as opposed to a false
    dichotomy engendered by P values.
    An estimation plot has two key features:
    1. It presents all datapoints as a swarmplot, which orders each point to
    display the underlying distribution.
    2. It presents the effect size as a bootstrap 95% confidence interval on a
    separate but aligned axes.
    Estimation plots are introduced in Ho et al., Nature Methods 2019, 1548-7105.
    <doi:10.1038/s41592-019-0470-3>.
    The free-to-view PDF is located at <https://rdcu.be/bHhJ4>.
License: file LICENSE
URL: https://github.com/ACCLAB/dabestr
BugReports: https://github.com/ACCLAB/dabestr/issues
Encoding: UTF-8
LazyData: true
Depends:
    R (>= 3.5.0),
    magrittr,
    stats,
    utils
Imports:
    boot,
    cowplot,
    dplyr,
    effsize,
    ellipsis,
    ggplot2 (>= 3.2),
    forcats,
    ggforce,
    ggbeeswarm,
    plyr,
    RColorBrewer,
    rlang,
    simpleboot,
    stringr,
    tibble,
    tidyr,
RoxygenNote: 7.1.0
Suggests:
    knitr,
    rmarkdown,
    tufte,
    testthat,
    vdiffr
VignetteBuilder: knitr