Software
- GLM-BAR: Scalable sparse regression for massive generalized linear models via broken adaptive ridge
- BAR: A Surrogate Sparse Cox’s Regression with Applications to Sparse High-Dimensional Massive Sample Size Time-to-Event Data
- BJASS method using Matlab: A New Joint Screening Method for Right-Censored Survival Data with Ultrahigh Dimensional Covariates
- powerCompRisk: A power analysis tool for joint testing of cause-specific hazard and overall hazard
- JMcmprsk: An R package to fit joint models of continuous or ordinal longitudinal data and time-to-event data with competing risks
- ZIBseq: Detect abundance differences across clinical conditions
- controlTest: An R package for two-sample nonparametric comparison of survival quantiles
- R Code for E-BJ algorithm
- R Code for Nonparametric comparison of ROC curves from Clustered Data
- C Program for Joint Modeling of Longitudinal Measurements and Competing Risks Failure Time Data
- LRci.surv: R Function for Likelihood Ratio Based Confidence Intervals for A Survival Probability
- PAmeasures: Prediction and Accuracy Measures for Nonlinear Models and for Right-Censored Time-to-Event Data
- Fastcmprsk: Fine-Gray Regression via Forward-Backward Scan
- BrokenAdaptiveRidge: An R package for performing L_0-based regressions using Cyclops
- ELMCoxBAR - Extreme Learning Machine Cox Model for High Dimensional Survival Analysis
- JMcmprsk - An R Package for Joint Modelling of Longitudinal and Survival Data with Competing Risks.
- BJASS – Matlab code for BJASS joint screening method
- CenBAR – An R package for Broken Adaptive Ridge AFT Model with Censored Data