Joint Frailty-Copula Models for Tumour Progression and Death in Meta-Analysis

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) , Emura et al. (2018) , Emura et al. (2019) , and Wu et al. 2020 . See also the book of Emura et al. (2019) . Survival data from ovarian cancer patients are also available.


Reference manual

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3.8 by Takeshi Emura, 5 months ago

Browse source code at

Authors: Takeshi Emura

Documentation:   PDF Manual  

Task views: Meta-Analysis, Survival Analysis

GPL-2 license

Depends on survival

Depended on by GFGM.copula.

See at CRAN