CRAN/E | SMARTAR

SMARTAR

Sequential Multiple Assignment Randomized Trial and Adaptive Randomization

Installation

About

Primary data analysis for sequential multiple assignment randomization trial (SMART) and calibration tools for clinical trial planning purposes. \n The methods used for this package include: \n (1) Likelihood-based global test (hypothesis test, power calculation) by in Zhong X., Cheng, B., Qian M., Cheung Y.K. (2019) doi:10.1016/j.cct.2019.105830. \n (2) IPWE-based global test (hypotehsis test, power calculation) by Ogbagaber S.B., Karp J., Wahed A.S. (2016) doi:10.1002/sim.6747. \n (3) G estimates (pairwise comparison, power calculation) by Lavori R., Dawson P.W. (2012) doi:10.1093/biostatistics/kxr016. \n (4) IPW estimates (pairwise comparison, power calculation) by Murphy S.A. (2005) doi:10.1002/sim.2022. \n (5) SAMRT with adaptive randomization by Cheung Y.K. (2015) doi:10.1111/biom.12258.

github.com/tonizhong/SMARTAR/
Bug report File report

Key Metrics

Version 1.1.0
R ≥ 3.5.0
Published 2020-07-30 1221 days ago
Needs compilation? no
License MIT
License File
CRAN checks SMARTAR results

Downloads

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Maintainer

Maintainer

Tony Zhong

xiaobo.zhong@mountsinai.org

Authors

Tony Zhong \n Xinru Wang \n Bin Cheng \n Ying Kuen Cheung

Material

README
NEWS
Reference manual
Package source

Vignettes

SMARTAR-tutorial

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

SMARTAR archive

Depends

R ≥ 3.5.0

Imports

graphics
MASS
stats

Suggests

knitr
rmarkdown
testthat