Package: bulkQC 1.1
bulkQC: Quality Control and Outlier Identification in Bulk for Multicenter Trials
Multicenter randomized trials involve the collection and analysis of data from numerous study participants across multiple sites. Outliers may be present. To identify outliers, this package examines data at the individual level (univariate and multivariate) and site-level (with and without covariate adjustment). Methods are outlined in further detail in Rigdon et al (to appear).
Authors:
bulkQC_1.1.tar.gz
bulkQC_1.1.zip(r-4.7-any)bulkQC_1.1.zip(r-4.6-any)bulkQC_1.1.zip(r-4.5-any)
bulkQC_1.1.tgz(r-4.6-any)bulkQC_1.1.tgz(r-4.5-any)
bulkQC_1.1.tar.gz(r-4.7-any)bulkQC_1.1.tar.gz(r-4.6-any)
bulkQC_1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
bulkQC/json (API)
| # Install 'bulkQC' in R: |
| install.packages('bulkQC', repos = c('https://joerigdon.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:7f69749ab1. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 98 | ||
| source / vignettes | OK | 138 | ||
| linux-release | OK | 87 | ||
| macos-release | OK | 149 | ||
| macos-oldrel | OK | 204 | ||
| windows-devel | OK | 73 | ||
| windows-release | OK | 56 | ||
| windows-oldrel | OK | 66 | ||
| wasm-release | OK | 79 |
Exports:getOutliersind_multiind_uninValsite_outliers
Dependencies:isotreejsonliteRcppRhpcBLASctlstddiff
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Quality Control and Outlier Identification in Bulk for Multicenter Trials | bulkQC-package |
| Function to obtain values outside of whiskers on boxplot | getOutliers |
| Identifies individual multivariate outliers | ind_multi |
| Identifies individual univariate outliers | ind_uni |
| Unique values in a vector | nVal |
| Identifies site level outliers | site_outliers |