surrosurv

R package surrosurv. Evaluation of Failure Time Surrogate Endpoints in Individual Patient Data Meta-Analyses. Provides functions for the evaluation of surrogate endpoints when both the surrogate and the true endpoint are failure time variables. The approaches implemented are: (1) the two-step approach (Burzykowski et al, 2001) <<a href=”http://dx.doi.org/10.1111/1467-9876.00244”>doi:10.1111/1467-9876.00244</a>> with a copula model (Clayton, Plackett, Hougaard) at the first step and either a linear regression of log-hazard ratios at the second step (either adjusted or not for measurement error); (2) mixed proportional hazard models estimated via mixed Poisson GLM.

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References in zbMATH (referenced in 4 articles )

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  1. Huang, Xin-Wei; Emura, Takeshi: Model diagnostic procedures for copula-based Markov chain models for statistical process control (2021)
  2. Huang, Xin-Wei; Wang, Weijing; Emura, Takeshi: A copula-based Markov chain model for serially dependent event times with a dependent terminal event (2021)
  3. Wu, Bo-Hong; Michimae, Hirofumi; Emura, Takeshi: Meta-analysis of individual patient data with semi-competing risks under the Weibull joint frailty-copula model (2020)
  4. Shih, Jia-Han; Konno, Yoshihiko; Chang, Yuan-Tsung; Emura, Takeshi: Estimation of a common mean vector in bivariate meta-analysis under the FGM copula (2019)