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
[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:
Downloads:
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