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1 | 1 | Package: dabestr |
2 | 2 | Type: Package |
3 | 3 | Title: Data Analysis using Bootstrap-Coupled Estimation |
4 | | -Version: 0.3.0 |
| 4 | +Version: 2023.9.12 |
5 | 5 | Authors@R: c( |
6 | | - person("Joses W.", "Ho", |
7 | | - email = "joseshowh@gmail.com", role = c("cre", "aut")), |
8 | | - person("Tayfun", "Tumkaya", |
9 | | - role = c("aut")) |
10 | | - ) |
11 | | -Maintainer: Joses W. Ho <joseshowh@gmail.com> |
| 6 | + person("Yishan", "Mai", email = "maiyishan@u.duke.nus.edu", role = c("cre", "ctb"), |
| 7 | + comment = c(ORCID = "0000-0002-7199-380X")), |
| 8 | + person("Kah Seng", "Lian", email = "kahseng@u.nus.edu", role = c("aut")), |
| 9 | + person("Zhuoyu", "Wang", email = "wzhuoyu21@u.nus,edu", role = "aut"), |
| 10 | + person("Jun Yang", "Liao", email = "name@example.com", role = "aut"), |
| 11 | + person("Joses W.", "Ho", email = "joseshowh@gmail.com", role = "aut", |
| 12 | + comment = c(ORCID = "0000-0002-9186-6322")), |
| 13 | + person("Tayfun", "Tumkaya", role = "aut", |
| 14 | + comment = c(ORCID = "0000-0001-8425-3360")), |
| 15 | + person("Felicia", "Low", role = "aut", email = "lowminhuifelicia@gmail.com"), |
| 16 | + person("Adam", "Claridge-Chang", role = "ctb", |
| 17 | + comment = c(ORCID = "0000-0002-4583-3650")), |
| 18 | + person("Hyungwon", "Choi", role = "ctb", |
| 19 | + comment = c(ORCID = "0000-0002-6687-3088")), |
| 20 | + person("Sangyu", "Xu", role = "ctb", |
| 21 | + comment = c(ORCID = "0000-0002-4927-9204")), |
| 22 | + person("ACCLAB", role = c("cph", "fnd"))) |
12 | 23 | Description: Data Analysis using Bootstrap-Coupled ESTimation. |
13 | | - Estimation statistics is a simple framework that avoids the pitfalls of |
14 | | - significance testing. It uses familiar statistical concepts: means, |
15 | | - mean differences, and error bars. More importantly, it focuses on the |
16 | | - effect size of one's experiment/intervention, as opposed to a false |
17 | | - dichotomy engendered by P values. |
18 | | - An estimation plot has two key features: |
19 | | - 1. It presents all datapoints as a swarmplot, which orders each point to |
20 | | - display the underlying distribution. |
21 | | - 2. It presents the effect size as a bootstrap 95% confidence interval on a |
22 | | - separate but aligned axes. |
23 | | - Estimation plots are introduced in Ho et al., Nature Methods 2019, 1548-7105. |
24 | | - <doi:10.1038/s41592-019-0470-3>. |
25 | | - The free-to-view PDF is located at <https://rdcu.be/bHhJ4>. |
26 | | -License: file LICENSE |
27 | | -URL: https://github.com/ACCLAB/dabestr |
28 | | -BugReports: https://github.com/ACCLAB/dabestr/issues |
| 24 | + Estimation statistics is a simple framework that avoids the pitfalls of |
| 25 | + significance testing. It uses familiar statistical concepts: means, |
| 26 | + mean differences, and error bars. More importantly, it focuses on the |
| 27 | + effect size of one's experiment/intervention, as opposed to a false |
| 28 | + dichotomy engendered by P values. |
| 29 | + An estimation plot has two key features: |
| 30 | + 1. It presents all datapoints as a swarmplot, which orders each point to |
| 31 | + display the underlying distribution. |
| 32 | + 2. It presents the effect size as a bootstrap 95% confidence interval on a |
| 33 | + separate but aligned axes. |
| 34 | + Estimation plots are introduced in Ho et al., Nature Methods 2019, 1548-7105. |
| 35 | + <doi:10.1038/s41592-019-0470-3>. |
| 36 | + 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>. |
| 37 | +License: Apache License (>= 2) |
29 | 38 | Encoding: UTF-8 |
30 | | -LazyData: true |
| 39 | +URL: https://github.com/ACCLAB/dabestr, |
| 40 | + https://acclab.github.io/dabestr/ |
31 | 41 | Depends: |
32 | | - R (>= 3.5.0), |
33 | | - magrittr, |
34 | | - stats, |
35 | | - utils |
36 | | -Imports: |
37 | | - boot, |
38 | | - cowplot, |
39 | | - dplyr, |
40 | | - effsize, |
41 | | - ellipsis, |
42 | | - ggplot2 (>= 3.2), |
43 | | - forcats, |
44 | | - ggforce, |
45 | | - ggbeeswarm, |
46 | | - plyr, |
47 | | - RColorBrewer, |
48 | | - rlang, |
49 | | - simpleboot, |
50 | | - stringr, |
51 | | - tibble, |
52 | | - tidyr, |
53 | | -RoxygenNote: 7.1.0 |
54 | | -Suggests: |
| 42 | + R (>= 2.10) |
| 43 | +Imports: |
| 44 | + ggplot2, |
| 45 | + cowplot, |
| 46 | + tidyr, |
| 47 | + dplyr, |
| 48 | + tibble, |
| 49 | + rlang, |
| 50 | + magrittr, |
| 51 | + ggbeeswarm, |
| 52 | + effsize, |
| 53 | + grid, |
| 54 | + scales, |
| 55 | + ggsci, |
| 56 | + cli, |
| 57 | + boot, |
| 58 | + stats, |
| 59 | + stringr, |
| 60 | + brunnermunzel, |
| 61 | + methods |
| 62 | +Roxygen: list(markdown = TRUE) |
| 63 | +RoxygenNote: 7.2.3 |
| 64 | +Suggests: |
| 65 | + testthat (>= 3.0.0), |
| 66 | + vdiffr, |
55 | 67 | knitr, |
56 | 68 | rmarkdown, |
57 | | - tufte, |
58 | | - testthat, |
59 | | - vdiffr |
60 | | -VignetteBuilder: knitr |
| 69 | + kableExtra |
| 70 | +Config/testthat/edition: 3 |
| 71 | +LazyData: true |
| 72 | +VignetteBuilder: knitr, kableExtra |
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