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RCTRecruit: Non-Parametric Recruitment Prediction for Randomized Clinical Trials

Accurate prediction of subject recruitment for Randomized Clinical Trials (RCT) remains an ongoing challenge. Many previous prediction models rely on parametric assumptions. We present functions for non-parametric RCT recruitment prediction under several scenarios.

Version: 0.1.24
Depends: R (≥ 3.5)
Imports: lubridate, methods, Rcpp
LinkingTo: Rcpp
Suggests: knitr, magrittr, testthat (≥ 3.0.0), withr
Published: 2025-01-15
DOI: 10.32614/CRAN.package.RCTRecruit
Author: Ioannis Malagaris ORCID iD [aut, cre, cph], Alejandro Villasante-Tezanos [aut], Christopher Kurinec [aut], Xiaoying Yu [aut]
Maintainer: Ioannis Malagaris <iomalaga at utmb.edu>
BugReports: https://github.com/imalagaris/RCTRecruit/issues
License: MIT + file LICENSE
URL: https://github.com/imalagaris/RCTRecruit
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: RCTRecruit results

Documentation:

Reference manual: RCTRecruit.pdf

Downloads:

Package source: RCTRecruit_0.1.24.tar.gz
Windows binaries: r-devel: RCTRecruit_0.1.24.zip, r-release: RCTRecruit_0.1.24.zip, r-oldrel: RCTRecruit_0.1.24.zip
macOS binaries: r-release (arm64): RCTRecruit_0.1.24.tgz, r-oldrel (arm64): RCTRecruit_0.1.24.tgz, r-release (x86_64): RCTRecruit_0.1.24.tgz, r-oldrel (x86_64): RCTRecruit_0.1.24.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=RCTRecruit to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.