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joint.Cox  

Joint Frailty-Copula Models for Tumour Progression and Death in Meta-Analysis
View on CRAN: Click here


Download and install joint.Cox package within the R console
Install from CRAN:
install.packages("joint.Cox")

Install from Github:
library("remotes")
install_github("cran/joint.Cox")

Install by package version:
library("remotes")
install_version("joint.Cox", "3.16")



Attach the package and use:
library("joint.Cox")
Maintained by
Takeshi Emura
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-02-28
Latest Update: 2022-02-04
Description:
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.
How to cite:
Takeshi Emura (2015). joint.Cox: Joint Frailty-Copula Models for Tumour Progression and Death in Meta-Analysis. R package version 3.16, https://cran.r-project.org/web/packages/joint.Cox
Previous versions and publish date:
1.0 (2015-02-28 12:17), 1.1 (2015-05-24 13:09), 2.0 (2015-06-18 18:27), 2.1 (2015-09-25 14:39), 2.2 (2015-10-03 14:47), 2.3 (2015-10-23 08:50), 2.4 (2016-02-24 12:07), 2.5 (2016-05-05 16:01), 2.6 (2016-06-04 07:52), 2.7 (2016-09-21 15:41), 2.8 (2016-09-30 23:19), 2.9 (2016-10-22 17:52), 2.10 (2016-10-30 11:39), 2.11 (2017-04-16 09:15), 2.12 (2017-05-01 12:20), 2.13 (2017-09-03 11:25), 2.14 (2017-11-23 15:23), 2.15 (2018-05-29 07:12), 2.16 (2018-07-13 12:00), 3.1 (2019-01-03 11:50), 3.2 (2019-05-16 13:20), 3.3 (2019-06-12 10:20), 3.4 (2019-07-18 08:36), 3.5 (2019-09-08 16:00), 3.6 (2019-09-17 06:50), 3.7 (2019-11-20 11:40), 3.8 (2020-05-25 11:00), 3.9 (2020-11-04 09:30), 3.10 (2020-12-08 11:20), 3.11 (2021-04-24 13:40), 3.12 (2021-05-13 15:10), 3.13 (2021-06-13 06:40), 3.14 (2021-07-03 06:40), 3.15 (2021-10-29 08:10)
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