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: | 0.2.0 |
| Depends: | R (≥ 4.2.0) |
| Imports: | lubridate, methods, Rcpp |
| LinkingTo: | Rcpp |
| Suggests: | knitr, magrittr, testthat (≥ 3.0.0), withr |
| Published: | 2025-04-21 |
| DOI: | 10.32614/CRAN.package.RCTRecruit |
| Author: | Ioannis Malagaris |
| 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 |
| Reference manual: | RCTRecruit.html , RCTRecruit.pdf |
| Package source: | RCTRecruit_0.2.0.tar.gz |
| Windows binaries: | r-devel: RCTRecruit_0.2.0.zip, r-release: RCTRecruit_0.2.0.zip, r-oldrel: RCTRecruit_0.2.0.zip |
| macOS binaries: | r-release (arm64): RCTRecruit_0.2.0.tgz, r-oldrel (arm64): RCTRecruit_0.2.0.tgz, r-release (x86_64): RCTRecruit_0.2.0.tgz, r-oldrel (x86_64): RCTRecruit_0.2.0.tgz |
| Old sources: | RCTRecruit archive |
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