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:

References in zbMATH (referenced in 147 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. Blanche, Paul: Confidence intervals for the cumulative incidence function via constrained NPMLE (2020)
  3. 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
  4. Gupta, Bhisham C.; Guttman, Irwin; Jayalath, Kalanka P.: Statistics and probability with applications for engineers and scientists using MINITAB, R and JMP (2020)
  5. 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
  6. Torsten Hothorn: Most Likely Transformations: The mlt Package (2020) not zbMATH
  7. 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
  8. Barreto-Souza, Wagner; Mayrink, Vinícius Diniz: Semiparametric generalized exponential frailty model for clustered survival data (2019)
  9. Di Caterina, Claudia; Cortese, Giuliana; Sartori, Nicola: Monte Carlo modified profile likelihood in models for clustered data (2019)
  10. Dobler, Dennis: Bootstrapping the Kaplan-Meier estimator on the whole line (2019)
  11. Emura, Takeshi; Matsui, Shigeyuki; Rondeau, Virginie: Survival analysis with correlated endpoints. Joint frailty-copula models (2019)
  12. Haller, Bernhard; Ulm, Kurt; Hapfelmeier, Alexander: A simulation study comparing different statistical approaches for the identification of predictive biomarkers (2019)
  13. 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)
  14. Keiding, Niels; Albertsen, Katrine Lykke; Rytgaard, Helene Charlotte; Sørensen, Anne Lyngholm: Prevalent cohort studies and unobserved heterogeneity (2019)
  15. Kvamme, Håvard; Borgan, Ørnulf; Scheel, Ida: Time-to-event prediction with neural networks and Cox regression (2019)
  16. Shih, Jia-Han; Emura, Takeshi: Bivariate dependence measures and bivariate competing risks models under the generalized FGM copula (2019)
  17. Shi, Yueyong; Xu, Deyi; Cao, Yongxiu; Jiao, Yuling: Variable selection via generalized SELO-penalized Cox regression models (2019)
  18. Theodor Balan; Hein Putter: frailtyEM: An R Package for Estimating Semiparametric Shared Frailty Models (2019) not zbMATH
  19. Brown, Jonathon D.: Advanced statistics for the behavioral sciences. A computational approach with R (2018)
  20. Chenguang Wang; Thomas Louis; Nicholas Henderson; Carlos Weiss; Ravi Varadhan: beanz: An R Package for Bayesian Analysis of Heterogeneous Treatment Effects with a Graphical User Interface (2018) not zbMATH

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