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

Downloads:

Reference manual: SMARTp.pdf
Package source: SMARTp_0.1.1.tar.gz
Windows binaries: r-devel: SMARTp_0.1.1.zip, r-devel-gcc8: SMARTp_0.1.1.zip, r-release: SMARTp_0.1.1.zip, r-oldrel: SMARTp_0.1.1.zip
OS X binaries: r-release: SMARTp_0.1.1.tgz, r-oldrel: SMARTp_0.1.1.tgz

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