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Graphical approach provides a useful framework for multiplicity adjustment in clinical trials with multiple endpoints. This package includes statistical methods to optimize sample size over initial weight and transition probability in a graphical approach under a common setting, which is to use marginal power for each endpoint in a trial design. See Zhang, F. and Gou, J. (2023). Sample size optimization for clinical trials using graphical approaches for multiplicity adjustment, Technical Report.
| Version: | 1.0.0 |
| Depends: | R (≥ 4.2.0) |
| Imports: | GA (≥ 3.0.0), graphics (≥ 4.2.0), mvtnorm (≥ 1.1.0), stats (≥ 4.0.0) |
| Published: | 2023-08-17 |
| Author: | Jiangtao Gou [aut, cre], Fengqing (Zoe) Zhang [aut] |
| Maintainer: | Jiangtao Gou <gouRpackage at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | graposas results |
| Reference manual: | graposas.pdf |
| Package source: | graposas_1.0.0.tar.gz |
| Windows binaries: | r-devel: graposas_1.0.0.zip, r-release: graposas_1.0.0.zip, r-oldrel: graposas_1.0.0.zip |
| macOS binaries: | r-release (arm64): graposas_1.0.0.tgz, r-oldrel (arm64): graposas_1.0.0.tgz, r-release (x86_64): graposas_1.0.0.tgz, r-oldrel (x86_64): graposas_1.0.0.tgz |
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