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.

Version: 2.13
Depends: survival
Published: 2017-09-03
Author: Takeshi Emura
Maintainer: Takeshi Emura <takeshiemura at gmail.com>
License: GPL-2
NeedsCompilation: no
In views: MetaAnalysis, Survival
CRAN checks: joint.Cox results

Downloads:

Reference manual: joint.Cox.pdf
Package source: joint.Cox_2.13.tar.gz
Windows binaries: r-devel: joint.Cox_2.13.zip, r-release: joint.Cox_2.13.zip, r-oldrel: joint.Cox_2.13.zip
OS X El Capitan binaries: r-release: joint.Cox_2.13.tgz
OS X Mavericks binaries: r-oldrel: joint.Cox_2.13.tgz
Old sources: joint.Cox archive

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