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. (2020) , Shinohara et al. (2020) , Wu et al. (2020) , and Emura et al. (2021) . See also the book of Emura et al. (2019) . Survival data from ovarian cancer patients are also available.


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


3.15 by Takeshi Emura, a month 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