joint.Cox

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.

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