Package: dabestr
Type: Package
Title: Data Analysis using Bootstrap-Coupled Estimation
Version: 0.2.0
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 (2018) <doi:10.1101/377978>.
License: file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0), boot, magrittr
Imports: cowplot, dplyr, ggplot2 (>= 3.0), forcats, ggforce,
        ggbeeswarm, rlang, simpleboot, stringr, tibble, tidyr
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, tufte, testthat, vdiffr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-01-05 10:25:54 UTC; jacuzzijo
Author: Joses W. Ho [cre, aut],
  Tayfun Tumkaya [aut]
Repository: CRAN
Date/Publication: 2019-01-07 19:10:04 UTC
