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 154 articles )

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  1. Abid, Rahma; Kokonendji, Célestin C.; Masmoudi, Afif: Geometric Tweedie regression models for continuous and semicontinuous data with variation phenomenon (2020)
  2. Achim Zeileis, Susanne Köll, Nathaniel Graham: Various Versatile Variances: An Object-Oriented Implementation of Clustered Covariances in R (2020) not zbMATH
  3. Blanche, Paul: Confidence intervals for the cumulative incidence function via constrained NPMLE (2020)
  4. 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
  5. Gupta, Bhisham C.; Guttman, Irwin; Jayalath, Kalanka P.: Statistics and probability with applications for engineers and scientists using MINITAB, R and JMP (2020)
  6. Haider, Humza; Hoehn, Bret; Davis, Sarah; Greiner, Russell: Effective ways to build and evaluate individual survival distributions (2020)
  7. Matthias Speidel, Jörg Drechsler, Shahab Jolani: The R Package hmi: A Convenient Tool for Hierarchical Multiple Imputation and Beyond (2020) not zbMATH
  8. 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
  9. Torsten Hothorn: Most Likely Transformations: The mlt Package (2020) not zbMATH
  10. 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
  11. Barreto-Souza, Wagner; Mayrink, Vinícius Diniz: Semiparametric generalized exponential frailty model for clustered survival data (2019)
  12. Di Caterina, Claudia; Cortese, Giuliana; Sartori, Nicola: Monte Carlo modified profile likelihood in models for clustered data (2019)
  13. Dobler, Dennis: Bootstrapping the Kaplan-Meier estimator on the whole line (2019)
  14. Emura, Takeshi; Matsui, Shigeyuki; Rondeau, Virginie: Survival analysis with correlated endpoints. Joint frailty-copula models (2019)
  15. Haller, Bernhard; Ulm, Kurt; Hapfelmeier, Alexander: A simulation study comparing different statistical approaches for the identification of predictive biomarkers (2019)
  16. Jaeger, Byron C.; Long, D. Leann; Long, Dustin M.; Sims, Mario; Szychowski, Jeff M.; Min, Yuan-I; McClure, Leslie A.; Howard, George; Simon, Noah: Oblique random survival forests (2019)
  17. Keiding, Niels; Albertsen, Katrine Lykke; Rytgaard, Helene Charlotte; Sørensen, Anne Lyngholm: Prevalent cohort studies and unobserved heterogeneity (2019)
  18. Kvamme, Håvard; Borgan, Ørnulf; Scheel, Ida: Time-to-event prediction with neural networks and Cox regression (2019)
  19. Shih, Jia-Han; Emura, Takeshi: Bivariate dependence measures and bivariate competing risks models under the generalized FGM copula (2019)
  20. Shi, Yueyong; Xu, Deyi; Cao, Yongxiu; Jiao, Yuling: Variable selection via generalized SELO-penalized Cox regression models (2019)

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