Joint Frailty-Copula Models for Tumour Progression and Death in Meta-Analysis R package joint.Cox version 3.16 CRAN Task View: MetaAnalysis (https://CRAN.R-project.org/view=MetaAnalysis) CRAN Task View: Survival (https://CRAN.R-project.org/view=Survival) Fit survival data and perform dynamic prediction under joint frailty-copula models for tumour progression and death. Likelihood-based methods are employed for estimating model parameters, where the baseline hazard functions are modeled by the cubic M-spline or the Weibull model. The methods are applicable for meta-analytic data containing individual-patient information from several studies. Survival outcomes need information on both terminal event time (e.g., time-to-death) and non-terminal event time (e.g., time-to-tumour progression). Methodologies were published in Emura et al. (2017) <doi:10.1177/0962280215604510>, Emura et al. (2018) <doi:10.1177/0962280216688032>, Emura et al. (2020) <doi:10.1177/0962280219892295>, Shinohara et al. (2020) <doi:10.1080/03610918.2020.1855449>, Wu et al. (2020) <doi:10.1007/s00180-020-00977-1>, and Emura et al. (2021) <doi:10.1177/09622802211046390>. See also the book of Emura et al. (2019) <doi:10.1007/978-981-13-3516-7>. Survival data from ovarian cancer patients are also available. Software Depends: survival Takeshi Emura <takeshiemura@gmail.com> Comprehensive R Archive Network (CRAN) Takeshi Emura GPL-2 2022-02-04 application/tgz https://CRAN.R-project.org/package=joint.Cox doi:10.32614/CRAN.package.joint.Cox