Plan optimal sample size allocation and go/no-go decision rules for phase II/III drug development programs with time-to-event, binary or normally distributed endpoints when assuming fixed treatment effects or a prior distribution for the treatment effect, using methods from Kirchner et al. (2016) <doi:10.1002/sim.6624> and Preussler (2020). Optimal is in the sense of maximal expected utility, where the utility is a function taking into account the expected cost and benefit of the program. It is possible to extend to more complex settings with bias correction (Preussler S et al. (2020) <doi:10.1186/s12874-020-01093-w>), multiple phase III trials (Preussler et al. (2019) <doi:10.1002/bimj.201700241>), multi-arm trials (Preussler et al. (2019) <doi:10.1080/19466315.2019.1702092>), and multiple endpoints (Kieser et al. (2018) <doi:10.1002/pst.1861>).
Version: 1.0.2 Depends: R (≥ 3.5.0), doParallel, parallel, foreach, iterators Imports: mvtnorm, cubature, msm, MASS, stats, progressr Suggests: rmarkdown, knitr, testthat (≥ 3.0.0), covr, kableExtra, magrittr, devtools Published: 2025-01-14 DOI: 10.32614/CRAN.package.drugdevelopR Author: Stella Erdmann [aut], Johannes Cepicka [aut], Marietta Kirchner [aut], Meinhard Kieser [aut], Lukas D. Sauer [aut, cre] Maintainer: Lukas D. Sauer <sauer at imbi.uni-heidelberg.de> BugReports: https://github.com/Sterniii3/drugdevelopR/issues License: MIT + file LICENSE URL: https://github.com/Sterniii3/drugdevelopR, https://sterniii3.github.io/drugdevelopR/ NeedsCompilation: no Materials: README NEWS CRAN checks: drugdevelopR results Documentation: Reference manual: drugdevelopR.pdf Vignettes: Bias adjustment - methods for discounting of phase II results (source, R code)Please use the canonical form https://CRAN.R-project.org/package=drugdevelopR to link to this page.
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