Scalable and Robust Latent Trajectory Class Analysis
Conduct latent trajectory class analysis with longitudinal data. Our method supports longitudinal continuous, binary and count data. For more methodological details, please refer to Hart, K.R., Fei, T. and Hanfelt, J.J. (2020), Scalable and robust latent trajectory class analysis using artificial likelihood. Biometrics <doi:10.1111/biom.13366>.
c(
person("Kari", "Hart", email = "khart@peddie.org", role = "aut"),
person("Teng", "Fei", email = "tfei@emory.edu", role = c("cre","aut"), comment = c(ORCID = "0000-0001-7888-1715")),
person("John", "Hanfelt", email = "jhanfel@emory.edu", role = "aut", comment = c(ORCID = "0000-0002-8488-6771"))
)

Miscellaneous Functions for analysis of gene expression data at SIRS-Lab GmbH
R(>= 2.4.0), stats, graphics, marray, limma, geneplotter, plotrix(>= 2.1.6)

R(>= 2.4.0), stats, graphics, plotrix(>= 2.1.6)

Sequential Multiple Assignment Randomized Trial and Adaptive
Randomization
Tony Zhong <xiaobo.zhong@mountsinai.org>
Bin Cheng <bc2159@cumc.columbia.edu>
Ying Kuen Cheung <yc632@cumc.columbia.edu>
Primary data analysis for sequential multiple assignment randomization trial (SMART) and calibration tools for clinical trial planning purposes.
The methods used for this package include:
(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>.
(2) IPWE-based global test (hypotehsis test, power calculation) by Ogbagaber S.B., Karp J., Wahed A.S. (2016) <doi:10.1002/sim.6747>.
(3) G estimates (pairwise comparison, power calculation) by  Lavori R., Dawson P.W. (2012) <doi:10.1093/biostatistics/kxr016>.
(4) IPW estimates (pairwise comparison, power calculation) by Murphy S.A. (2005) <doi:10.1002/sim.2022>.
(5) SAMRT with adaptive randomization by Cheung Y.K. (2015) <doi:10.1111/biom.12258>.

Tony 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>
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>.