tonizhong/SMARTAR: Sequential Multiple Assignment Randomized Trial and Adaptive Randomization

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>.

Getting started

Package details

AuthorTony Zhong <xiaobo.zhong@mountsinai.org> \n Xinru Wang <xw2676@cumc.columbia.edu> \n Bin Cheng <bc2159@cumc.columbia.edu> \n Ying Kuen Cheung <yc632@cumc.columbia.edu>
MaintainerTony Zhong <xiaobo.zhong@mountsinai.org>
LicenseMIT + file LICENSE
Version1.1.0
URL https://github.com/tonizhong/SMARTAR/
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("tonizhong/SMARTAR")
tonizhong/SMARTAR documentation built on Nov. 1, 2020, 2:40 p.m.