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DESCRIPTION
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Package: dabestr
Type: Package
Title: Data Analysis using Bootstrap-Coupled Estimation
Version: 2023.9.12
Authors@R: c(
person("Joses W.", "Ho", email = "[email protected]", role = "aut",
comment = c(ORCID = "0000-0002-9186-6322")),
person("Kah Seng", "Lian", email = "[email protected]", role = c("aut")),
person("Zhuoyu", "Wang", email = "[email protected],edu", role = "aut"),
person("Jun Yang", "Liao", email = "[email protected]", role = "aut"),
person("Felicia", "Low", role = "aut", email = "[email protected]"),
person("Tayfun", "Tumkaya", role = "aut",
comment = c(ORCID = "0000-0001-8425-3360")),
person("Yishan", "Mai", email = "[email protected]", role = c("cre", "ctb"),
comment = c(ORCID = "0000-0002-7199-380X")),
person("Sangyu", "Xu", role = "ctb",
comment = c(ORCID = "0000-0002-4927-9204")),
person("Hyungwon", "Choi", role = "ctb",
comment = c(ORCID = "0000-0002-6687-3088")),
person("Adam", "Claridge-Chang", role = "ctb",
comment = c(ORCID = "0000-0002-4583-3650")),
person("ACCLAB", role = c("cph", "fnd")))
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://www.nature.com/articles/s41592-019-0470-3.epdf?author_access_token=Euy6APITxsYA3huBKOFBvNRgN0jAjWel9jnR3ZoTv0Pr6zJiJ3AA5aH4989gOJS_dajtNr1Wt17D0fh-t4GFcvqwMYN03qb8C33na_UrCUcGrt-Z0J9aPL6TPSbOxIC-pbHWKUDo2XsUOr3hQmlRew%3D%3D>.
License: Apache License (>= 2)
Encoding: UTF-8
URL: https://github.com/ACCLAB/dabestr,
https://acclab.github.io/dabestr/
Depends:
R (>= 2.10)
Imports:
ggplot2,
cowplot,
tidyr,
dplyr,
tibble,
rlang,
magrittr,
ggbeeswarm,
effsize,
grid,
scales,
ggsci,
cli,
boot,
stats,
stringr,
brunnermunzel,
methods
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
Suggests:
testthat (>= 3.0.0),
vdiffr,
knitr,
rmarkdown,
kableExtra
Config/testthat/edition: 3
LazyData: true
VignetteBuilder: knitr, kableExtra