Package: dabestr 2023.9.12

Yishan Mai

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>.

Authors: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]

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Bug tracker:https://github.com/acclab/dabestr/issues

On CRAN:

data-analysisdata-visualizationestimationstatistics

9 exports 215 stars 5.97 score 44 dependencies 16 mentions 135 scripts 484 downloads

Last updated 11 months agofrom:74a9d60e12. Checks:OK: 7. Indexed: yes.

Exports:%>%cliffs_deltacohens_dcohens_hdabest_plothedges_gloadmean_diffmedian_diff

Dependencies:beeswarmbootbrunnermunzelclicolorspacecowplotcpp11dplyreffsizefansifarvergenericsggbeeswarmggplot2ggscigluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigpurrrR6RColorBrewerrlangscalesstringistringrtibbletidyrtidyselectutf8vctrsviporviridisLitewithr