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>.
| Version: | 0.2.0 |
| Depends: | R (≥ 3.5.0), boot, magrittr |
| Imports: | cowplot, dplyr, ggplot2 (≥ 3.0), forcats, ggforce, ggbeeswarm, rlang, simpleboot, stringr, tibble, tidyr |
| Suggests: | knitr, rmarkdown, tufte, testthat, vdiffr |
| Published: | 2019-01-07 |
| Author: | Joses W. Ho [cre, aut], Tayfun Tumkaya [aut] |
| Maintainer: | Joses W. Ho <joseshowh at gmail.com> |
| License: | file LICENSE |
| NeedsCompilation: | no |
| Citation: | dabestr citation info |
| Materials: | README |
| CRAN checks: | dabestr results |
| Reference manual: | dabestr.pdf |
| Vignettes: |
Bootstrap Confidence Intervals Robust and Beautiful Statistical Visualization Using dabestr |
| Package source: | dabestr_0.2.0.tar.gz |
| Windows binaries: | r-devel: dabestr_0.2.0.zip, r-release: dabestr_0.2.0.zip, r-oldrel: dabestr_0.2.0.zip |
| OS X binaries: | r-release: dabestr_0.2.0.tgz, r-oldrel: dabestr_0.2.0.tgz |
| Old sources: | dabestr archive |
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