joint.Cox: Penalized Likelihood Estimation and Dynamic Prediction under the Joint Frailty-Copula Models Between Tumour Progression and Death for Meta-Analysis

Perform the Cox regression and dynamic prediction methods under the joint frailty-copula model between tumour progression and death for meta-analysis. A penalized likelihood is employed for estimating model parameters, where the baseline hazard functions are approximated by smoothing splines. The methods are applicable for meta-analytic data combining several studies. The methods can analyze data having information on both terminal event time (e.g., time-to-death) and non-terminal event time (e.g., time-to-tumour progression). See Emura et al. (2015) <doi:10.1177/0962280215604510> and Emura et al. (2017) <doi:10.1177/0962280216688032> for details. Survival data from ovarian cancer patients are also available.

Install the latest version of this package by entering the following in R:
install.packages("joint.Cox")
AuthorTakeshi Emura
Date of publication2017-04-16 07:15:03 UTC
MaintainerTakeshi Emura <takeshiemura@gmail.com>
LicenseGPL-2
Version2.11

View on CRAN

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.