survival

R package survival: Survival analysis, including penalised likelihood , survival analysis: descriptive statistics, two-sample tests, parametric accelerated failure models, Cox model. Delayed entry (truncation) allowed for all models; interval censoring for parametric models. Case-cohort designs. (Source: http://cran.r-project.org/web/packages)


References in zbMATH (referenced in 170 articles )

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  1. Bivand, Roger S.; Gómez-Rubio, Virgilio: Spatial survival modelling of business re-opening after Katrina: survival modelling compared to spatial probit modelling of re-opening within 3, 6 or 12 months (2021)
  2. Hong Zhang, Qing Li, Devan V. Mehrotra, Judong Shen: CauchyCP: a powerful test under non-proportional hazards using Cauchy combination of change-point Cox regressions (2021) arXiv
  3. Jasper B. Yang, Bryan E. Shepherd, Thomas Lumley, Pamela A. Shaw: Optimum Allocation for Adaptive Multi-Wave Sampling in R: The R Package optimall (2021) arXiv
  4. Martin Bladt; Jorge Yslas: matrixdist: An R Package for Inhomogeneous Phase-Type Distributions (2021) arXiv
  5. McPhedran, Robert; Toombs, Ben: Efficacy or delivery? An online discrete choice experiment to explore preferences for COVID-19 vaccines in the UK (2021)
  6. Sy Han Chiou, Gongjun Xu, Jun Yan, Chiung-Yu Huang: Regression Modeling for Recurrent Events Using R Package reReg (2021) arXiv
  7. Yun-Hee Choi, Laurent Briollais, Wenqing He, Karen Kopciuk: FamEvent: An R Package for Generating and Modeling Time-to-Event Data in Family Designs (2021) not zbMATH
  8. Yu, Yi; Bradic, Jelena; Samworth, Richard J.: Confidence intervals for high-dimensional Cox models (2021)
  9. Abid, Rahma; Kokonendji, Célestin C.; Masmoudi, Afif: Geometric Tweedie regression models for continuous and semicontinuous data with variation phenomenon (2020)
  10. Achim Zeileis, Susanne Köll, Nathaniel Graham: Various Versatile Variances: An Object-Oriented Implementation of Clustered Covariances in R (2020) not zbMATH
  11. Blanche, Paul: Confidence intervals for the cumulative incidence function via constrained NPMLE (2020)
  12. Canhong Wen, Aijun Zhang, Shijie Quan, Xueqin Wang: BeSS: An R Package for Best Subset Selection in Linear, Logistic and Cox Proportional Hazards Models (2020) not zbMATH
  13. Gupta, Bhisham C.; Guttman, Irwin; Jayalath, Kalanka P.: Statistics and probability with applications for engineers and scientists using MINITAB, R and JMP (2020)
  14. Haider, Humza; Hoehn, Bret; Davis, Sarah; Greiner, Russell: Effective ways to build and evaluate individual survival distributions (2020)
  15. Matthias Speidel, Jörg Drechsler, Shahab Jolani: The R Package hmi: A Convenient Tool for Hierarchical Multiple Imputation and Beyond (2020) not zbMATH
  16. Minnie M. Joo, Nicolás Schmidt, Sergio Béjar, Vineeta Yadav, Bumba Mukherjee: BayesMFSurv: An R Package to Estimate Bayesian Split-Population Survival Models With (and Without) Misclassified Failure Events (2020) not zbMATH
  17. Parkinson, Judith H.: Combined multiple testing of multivariate survival times by censored empirical likelihood (2020)
  18. Torsten Hothorn: Most Likely Transformations: The mlt Package (2020) not zbMATH
  19. Alireza S. Mahani; Mansour T.A. Sharabiani: Bayesian, and Non-Bayesian, Cause-Specific Competing-Risk Analysis for Parametric and Nonparametric Survival Functions: The R Package CFC (2019) not zbMATH
  20. Barreto-Souza, Wagner; Mayrink, Vinícius Diniz: Semiparametric generalized exponential frailty model for clustered survival data (2019)

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