Packaged: 2021-07-15 12:24:16 UTC; armin.rauschenberger

Packaged: 2021-07-16 11:46:43 UTC; armin.rauschenberger

Title: Penalized Likelihood Estimation under the Joint Cox Models
Description: Perform regression analyses under the joint Cox proportional hazards model between TTP and OS for meta-analysis.
The method is applicable for meta-analysis combining several studies or for cluster survival data.

Between Tumour Progression and Death for Meta-Analysis
Description: Perform regression analyses under the joint Cox proportional hazards model between tumour progression and death for meta-analysis.

Title: Penalized Likelihood Estimation and Prediction under the Joint
Cox Models Between Tumour Progression and Death for

Title: Penalized Likelihood Estimation and Dynamic Prediction under the
Joint Frailty-Copula Models Between Tumour Progression and
Description: Perform the Cox regression and dynamic prediction under the joint frailty-copula model between tumour progression and death for meta-analysis.
The method is applicable for meta-analytic data combining several studies. The data should have information on both terminal event time (e.g., time-to-death) and non-terminal event time (e.g., time-to-tumour progression).

Description: Perform the Cox regression and dynamic prediction methods under
the joint frailty-copula model between tumour progression and death for meta-analysis.
A penalized likelihood is employed for estimating model parameters, where the baseline hazard functions are approximated by smoothing splines.
The methods are applicable for meta-analytic data combining several studies.
The methods can analyze data having information on both terminal event time (e.g., time-to-death) and non-terminal event time (e.g., time-to-tumour progression).
Survival data from ovarian cancer patients are also available.

The method is applicable for meta-analytic data combining several studies. The data should have information on both terminal event time (time-to-death) and non-terminal event time (time-to-tumour progression).