Package: intervcomp 0.1.2
Kimihiro Noguchi
intervcomp: Hypothesis Testing Using the Overlapping Interval Estimates
Performs hypothesis testing using the interval estimates (e.g., confidence intervals). The non-overlapping interval estimates indicates the statistical significance. References to these procedures can be found at Noguchi and Marmolejo-Ramos (2016) <doi:10.1080/00031305.2016.1200487>, Bonett and Seier (2003) <doi:10.1198/0003130032323>, and Lemm (2006) <doi:10.1300/J082v51n02_05>.
Authors:
intervcomp_0.1.2.tar.gz
intervcomp_0.1.2.tar.gz(r-4.7-any)intervcomp_0.1.2.tar.gz(r-4.6-any)
intervcomp_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
intervcomp/json (API)
| # Install 'intervcomp' in R: |
| install.packages('intervcomp', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- grouping - Grouping of Subjects for the Implicit Association Test
- reactiontimes - Reaction Time (RT) Data for the Implicit Association Test
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:90f97ea5b8. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 159 | ||
| source / vignettes | OK | 146 | ||
| linux-release-x86_64 | OK | 103 | ||
| wasm-release | OK | 98 |
Exports:Bonett.Seier.testdata.scale.xylogratiotwo.sample.meantwo.sample.var
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Bonett-Seier Test for Equality of Variability Measures | Bonett.Seier.test |
| Data Transformation for Testing Equality of Variability Measures | data.scale.xy |
| Grouping of Subjects for the Implicit Association Test | grouping |
| Log Ratio Analysis for the Implicit Association Test (IAT) | logratio |
| Reaction Time (RT) Data for the Implicit Association Test | reactiontimes |
| Range-Preserving Two-Sample T-Test for Equality of Means | two.sample.mean |
| Two-Sample T-Test for Equality of Variability Mesures | two.sample.var |