joint.Cox: Joint Frailty-Copula Models for Tumour Progression and Death in Meta-Analysis

Perform likelihood estimation and dynamic prediction under joint frailty-copula models for tumour progression and death in meta-analysis. A penalized likelihood method is employed for estimating model parameters, where the baseline hazard functions are modeled 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. (2017) <doi:10.1177/0962280215604510> for likelihood estimation, and Emura et al. (2018) <doi:10.1177/0962280216688032> for dynamic prediction. More details on these methods can also be found in a book of Emura et al. (2019) <doi:10.1007/978-981-13-3516-7>. Survival data from ovarian cancer patients are also available.

Version: 3.7
Depends: survival
Published: 2019-11-20
Author: Takeshi Emura
Maintainer: Takeshi Emura <takeshiemura at>
License: GPL-2
NeedsCompilation: no
In views: MetaAnalysis, Survival
CRAN checks: joint.Cox results


Reference manual: joint.Cox.pdf
Package source: joint.Cox_3.7.tar.gz
Windows binaries: r-devel:, r-devel-gcc8:, r-release:, r-oldrel:
OS X binaries: r-release: joint.Cox_3.7.tgz, r-oldrel: joint.Cox_3.7.tgz
Old sources: joint.Cox archive

Reverse dependencies:

Reverse depends: GFGM.copula


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