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Sample size calculation to detect dynamic treatment regime (DTR) effects based on change in clinical attachment level (CAL) outcomes from a non-surgical chronic periodontitis treatments study. The experiment is performed under a Sequential Multiple Assignment Randomized Trial (SMART) design. The clustered tooth (sub-unit) level CAL outcomes are skewed, spatially-referenced, and non-randomly missing. The implemented algorithm is available in Xu et al. (2019+) <doi:10.48550/arXiv.1902.09386>.
| Version: | 0.1.1 |
| Depends: | R (≥ 3.5) |
| Imports: | covr, sn (≥ 1.5), mvtnorm (≥ 1.0), stats, methods |
| Published: | 2019-05-17 |
| Author: | Jing Xu, Dipankar Bandyopadhyay, Douglas Azevedo, Bibhas Chakraborty |
| Maintainer: | Dipankar Bandyopadhyay <bandyopd at gmail.com> |
| License: | LGPL-2 | LGPL-2.1 | LGPL-3 [expanded from: LGPL (≥ 2)] |
| URL: | https://github.com/bandyopd/SMARTp |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | SMARTp results |
| Reference manual: | SMARTp.pdf |
| Package source: | SMARTp_0.1.1.tar.gz |
| Windows binaries: | r-devel: SMARTp_0.1.1.zip, r-release: SMARTp_0.1.1.zip, r-oldrel: SMARTp_0.1.1.zip |
| macOS binaries: | r-release (arm64): SMARTp_0.1.1.tgz, r-oldrel (arm64): SMARTp_0.1.1.tgz, r-release (x86_64): SMARTp_0.1.1.tgz, r-oldrel (x86_64): SMARTp_0.1.1.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.