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://rdcu.be/bHhJ4>.

Package details

AuthorJoses W. Ho [cre, aut], Tayfun Tumkaya [aut]
MaintainerJoses W. Ho <joseshowh@gmail.com>
Licensefile LICENSE
URL https://github.com/ACCLAB/dabestr
Package repositoryView on CRAN
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dabestr documentation built on July 13, 2020, 9:07 a.m.