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SMARTp: Sample Size for SMART Designs in Non-Surgical Periodontal Trials

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
DOI:	10.32614/CRAN.package.SMARTp
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

Documentation:

Reference manual:

SMARTp.html ,SMARTp.pdf

Downloads:

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

Linking:

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