accrualPlot: Accrual Plots and Predictions for Clinical Trials
Tracking accrual in clinical trials is important for trial success.
If accrual is too slow, the trial will take too long and be too expensive. If
accrual is much faster than expected, time sensitive tasks such as the writing
of statistical analysis plans might need to be rushed. 'accrualPlot' provides
functions to aid the tracking of accrual and predict when a trial will reach
it's intended sample size.
| Version: |
1.0.7 |
| Depends: |
lubridate, R (≥ 2.10) |
| Imports: |
dplyr, ggplot2, grid, magrittr, purrr, rlang |
| Suggests: |
knitr, markdown, patchwork, rmarkdown, testthat, vdiffr |
| Published: |
2022-08-16 |
| DOI: |
10.32614/CRAN.package.accrualPlot |
| Author: |
Lukas Bütikofer [cre, aut],
Alan G. Haynes [aut] |
| Maintainer: |
Lukas Bütikofer <lukas.buetikofer at ctu.unibe.ch> |
| BugReports: |
https://github.com/CTU-Bern/accrualPlot/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/CTU-Bern/accrualPlot,
https://ctu-bern.github.io/accrualPlot/ |
| NeedsCompilation: |
no |
| Materials: |
NEWS |
| In views: |
ClinicalTrials |
| CRAN checks: |
accrualPlot results |
Documentation:
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