dabestr: Data Analysis using Bootstrap-Coupled Estimation
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>.
| Version: |
2023.9.12 |
| Depends: |
R (≥ 2.10) |
| Imports: |
ggplot2, cowplot, tidyr, dplyr, tibble, rlang, magrittr, ggbeeswarm, effsize, grid, scales, ggsci, cli, boot, stats, stringr, brunnermunzel, methods |
| Suggests: |
testthat (≥ 3.0.0), vdiffr, knitr, rmarkdown, kableExtra |
| Published: |
2023-10-13 |
| DOI: |
10.32614/CRAN.package.dabestr |
| Author: |
Joses W. Ho  [aut],
Kah Seng Lian [aut],
Zhuoyu Wang [aut],
Jun Yang Liao [aut],
Felicia Low [aut],
Tayfun Tumkaya
[aut],
Yishan Mai [cre,
ctb],
Sangyu Xu [ctb],
Hyungwon Choi
[ctb],
Adam Claridge-Chang
[ctb],
ACCLAB [cph, fnd] |
| Maintainer: |
Yishan Mai <maiyishan at u.duke.nus.edu> |
| License: |
Apache License (≥ 2) |
| URL: |
https://github.com/ACCLAB/dabestr,
https://acclab.github.io/dabestr/ |
| NeedsCompilation: |
no |
| Citation: |
dabestr citation info |
| Materials: |
README NEWS |
| CRAN checks: |
dabestr results |
Documentation:
Downloads:
Reverse dependencies:
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