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+) <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

Documentation:

Reference manual:

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:

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