CRAN/E | dabestr

dabestr

Data Analysis using Bootstrap-Coupled Estimation

Installation

About

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 .

Citation dabestr citation info
github.com/ACCLAB/dabestr
acclab.github.io/dabestr/

Key Metrics

Version 2023.9.12
R ≥ 2.10
Published 2023-10-13 167 days ago
Needs compilation? no
License Apache License (≥ 2)
CRAN checks dabestr results

Downloads

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Maintainer

Maintainer

Yishan Mai

maiyishan@u.duke.nus.edu

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

Material

README
NEWS
Reference manual
Package source

Vignettes

Sample Datasets
Controlling Plot Aesthetics
Tutorial: Basics
Tutorial: Delta-Delta
Tutorial: Mini-Meta Delta
Tutorial: Proportion Plots
Tutorial: Repeated Measures

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

dabestr archive

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

Reverse Imports

permubiome