ppseq: Design Clinical Trials using Sequential Predictive Probability Monitoring

Functions are available to calibrate designs over a range of posterior and predictive thresholds, to plot the various design options, and to obtain the operating characteristics of optimal accuracy and optimal efficiency designs.

Version: 0.2.4
Depends: R (≥ 3.5.0)
Imports: dplyr, furrr, ggplot2, plotly, purrr, tibble, patchwork, tidyr
Suggests: covr, gt, knitr, rmarkdown, spelling, testthat (≥ 3.0.0), vdiffr
Published: 2024-04-04
DOI: 10.32614/CRAN.package.ppseq
Author: Emily C. Zabor ORCID iD [aut, cre], Brian P. Hobbs [aut], Michael J. Kane ORCID iD [aut]
Maintainer: Emily C. Zabor <zabore2 at ccf.org>
BugReports: https://github.com/zabore/ppseq/issues
License: MIT + file LICENSE
URL: https://github.com/zabore/ppseq, https://www.emilyzabor.com/ppseq/
NeedsCompilation: no
Language: en-US
Citation: ppseq citation info
Materials: README NEWS
CRAN checks: ppseq results


Reference manual: ppseq.pdf
Vignettes: One-sample expansion cohort
Two-sample randomized trial


Package source: ppseq_0.2.4.tar.gz
Windows binaries: r-devel: ppseq_0.2.4.zip, r-release: ppseq_0.2.4.zip, r-oldrel: ppseq_0.2.4.zip
macOS binaries: r-release (arm64): ppseq_0.2.4.tgz, r-oldrel (arm64): ppseq_0.2.4.tgz, r-release (x86_64): ppseq_0.2.4.tgz, r-oldrel (x86_64): ppseq_0.2.4.tgz
Old sources: ppseq archive


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