Group Sequential Design for a Clinical Trial with Censored
Survival Data
Sample size calculation utilizing the information fraction and the alpha spending function
in a group sequential clinical trial with censored survival data from underlying generalized
gamma survival distributions or log-logistic survival distributions.
Hsu, C.-H., Chen, C.-H, Hsu, K.-N. and Lu, Y.-H. (2018) A useful design utilizing the
information fraction in a group sequential clinical trial with censored survival data.
To appear in Biometrics.

High dimensional time to events data analysis with variable selection technique.
Currently support LASSO, clustering and Bonferroni's correction.
c(person(("Atanu"), "Bhattacharjee",
email="atanustat@gmail.com",
role=c("aut", "cre","ctb")),
person(("Akash"), "Pawar", role=c("aut","ctb")))
survival, utils, Rdpack (>= 0.7), readr, tidyverse, glmnet,
factoextra, igraph, useful
Atanu Bhattacharjee [aut, cre, ctb],
Akash Pawar [aut, ctb]

Analysis of Proportional Hazards Model with Sparse Longitudinal
Covariates
Hongyuan Cao, Mathew M. Churpek, Donglin Zeng, Jason P. Fine, and Shannon T. Holloway
Kernel weighting methods for estimation of proportional hazards models with intermittently observed longitudinal covariates.

Provides kernel weighting methods for estimation of proportional hazards models with intermittently observed longitudinal covariates. Cao H., Churpek M. M., Zeng D., and Fine J. P. (2015) <doi:10.1080/01621459.2014.957289>.

Hongyuan Cao, Mathew M. Churpek, Donglin Zeng, Jason P. Fine, and
Shannon T. Holloway
Provides kernel weighting methods for estimation of proportional
hazards models with intermittently observed longitudinal covariates.
Cao H., Churpek M. M., Zeng D., and Fine J. P. (2015)
<doi:10.1080/01621459.2014.957289>.

Multiple Imputation Method in Survival Analysis
survival (>= 3.1.11), zoo, stats, graphics, base
c(person("Yiming","Chen", email = "yimingc1208@gmail.com",role = c("aut", "cre")), person("John", "Lawrence", role="ctb"))
In clinical trials, endpoints are sometimes evaluated with uncertainty. Adjudication is commonly adopted to ensure the study integrity. We propose to use multiple imputation (MI) introduced by Robin (1987) <doi:10.1002/9780470316696> to incorporate these uncertainties if reasonable event probabilities were provided. The method has been applied to Cox Proportional Hazard (PH) model, Kaplan-Meier (KM) estimation and Log-rank test in this package. Moreover, weighted estimations discussed in Cook (2004) <doi:10.1016/S0197-2456(00)00053-2> were also implemented with weights calculated from event probabilities. In conclusion, this package can handle time-to-event analysis if events presented with uncertainty by different methods.
Yiming Chen [aut, cre],
John Lawrence [ctb]