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:Joseph Rigdon <[email protected]>

bulkQC_1.1.tar.gz
bulkQC_1.1.zip(r-4.5)bulkQC_1.1.zip(r-4.4)bulkQC_1.1.zip(r-4.3)
bulkQC_1.1.tgz(r-4.4-any)bulkQC_1.1.tgz(r-4.3-any)
bulkQC_1.1.tar.gz(r-4.5-noble)bulkQC_1.1.tar.gz(r-4.4-noble)
bulkQC_1.1.tgz(r-4.4-emscripten)bulkQC_1.1.tgz(r-4.3-emscripten)
bulkQC.pdf |bulkQC.html
bulkQC/json (API)

# Install 'bulkQC' in R:
install.packages('bulkQC', repos = c('https://joerigdon.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

5 exports 0.09 score 4 dependencies 889 downloads

Last updated 5 months agofrom:7f69749ab1. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 26 2024
R-4.5-winOKAug 26 2024
R-4.5-linuxOKAug 26 2024
R-4.4-winOKAug 26 2024
R-4.4-macOKAug 26 2024
R-4.3-winOKAug 26 2024
R-4.3-macOKAug 26 2024

Exports:getOutliersind_multiind_uninValsite_outliers

Dependencies:isotreejsonliteRcppstddiff