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 121 articles )

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  1. Di Caterina, Claudia; Cortese, Giuliana; Sartori, Nicola: Monte Carlo modified profile likelihood in models for clustered data (2019)
  2. Dobler, Dennis: Bootstrapping the Kaplan-Meier estimator on the whole line (2019)
  3. 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
  4. Chiou, Sy Han; Qian, Jing; Mormino, Elizabeth; Betensky, Rebecca A.: Permutation tests for general dependent truncation (2018)
  5. Daniela Dunkler; Meinhard Ploner; Michael Schemper; Georg Heinze: Weighted Cox Regression Using the R Package coxphw (2018) not zbMATH
  6. Dean, Natalie E.; Halloran, M. Elizabeth; Longini, Ira M.: Design of vaccine trials during outbreaks with and without a delayed vaccination comparator (2018)
  7. Diego Saldana; Yang Feng: SIS: An R Package for Sure Independence Screening in Ultrahigh-Dimensional Statistical Models (2018) not zbMATH
  8. Efromovich, Sam: Missing and modified data in nonparametric estimation: with R examples (2018)
  9. Higueras, Manuel; Howes, Adam: Poisson excess relative risk models: new implementations and software (2018)
  10. John Monaco; Malka Gorfine; Li Hsu: General Semiparametric Shared Frailty Model: Estimation and Simulation with frailtySurv (2018) not zbMATH
  11. Mandel, Micha; De Uña-Álvarez, Jacobo; Simon, David K.; Betensky, Rebecca A.: Inverse probability weighted Cox regression for doubly truncated data (2018)
  12. Peter Calhoun; Xiaogang Su;Martha Nunn; Juanjuan Fan: Constructing Multivariate Survival Trees: The MST Package for R (2018) not zbMATH
  13. Valliant, Richard; Dever, Jill A.; Kreuter, Frauke: Practical tools for designing and weighting survey samples (2018)
  14. Vanesa Balboa; Jacobo de Uña-Álvarez: Estimation of Transition Probabilities for the Illness-Death Model: Package TP.idm (2018) not zbMATH
  15. Xin, Xin; Horrocks, Julie; Darlington, Gerarda A.: Weighting methods for ties between event times and covariate change times (2018)
  16. Agnieszka Król; Audrey Mauguen; Yassin Mazroui; Alexandre Laurent; Stefan Michiels; Virginie Rondeau: Tutorial in Joint Modeling and Prediction: A Statistical Software for Correlated Longitudinal Outcomes, Recurrent Events and a Terminal Event (2017) not zbMATH
  17. Amélie Anota and Marion Savina and Caroline Bascoul-Mollevi and Franck Bonnetain: QoLR: An R Package for the Longitudinal Analysis of Health-Related Quality of Life in Oncology (2017) not zbMATH
  18. Antoine Filipovic-Pierucci, Kevin Zarca, Isabelle Durand-Zaleski: Markov Models for Health Economic Evaluations: The R Package heemod (2017) arXiv
  19. Balasubramanian Narasimhan and Daniel Rubin and Samuel Gross and Marina Bendersky and Philip Lavori: Software for Distributed Computation on Medical Databases: A Demonstration Project (2017) not zbMATH
  20. Célia Touraine and Thomas Gerds and Pierre Joly: SmoothHazard: An R Package for Fitting Regression Models to Interval-Censored Observations of Illness-Death Models (2017) not zbMATH

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