SemiMarkov

R package SemiMarkov: Multi-States Semi-Markov Models. Functions for fitting multi-state semi-Markov models to longitudinal data. A parametric maximum likelihood estimation method adapted to deal with Exponential, Weibull and Exponentiated Weibull distributions is considered. Right-censoring can be taken into account and both constant and time-varying covariates can be included using a Cox proportional model.

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References in zbMATH (referenced in 6 articles , 1 standard article )

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  1. Rui J. Costa, Moritz Gerstung: The R package ebmstate for disease progression analysis under empirical Bayes Cox models (2022) arXiv
  2. Chellai, Fatih: Determinants of birth-intervals in Algeria: a semi-Markov model analysis (2021)
  3. Danilo Alvares, Sebastien Haneuse, Catherine Lee, Kyu Ha Lee: SemiCompRisks: An R Package for Independent and Cluster-Correlated Analyses of Semi-Competing Risks Data (2018) arXiv
  4. Fuino, Michel; Wagner, Joël: Long-term care models and dependence probability tables by acuity level: new empirical evidence from Switzerland (2018)
  5. Guibert, Quentin; Planchet, Frédéric: Non-parametric inference of transition probabilities based on Aalen-Johansen integral estimators for acyclic multi-state models: application to LTC insurance (2018)
  6. Agnieszka Król; Philippe Saint-Pierre: SemiMarkov: An R Package for Parametric Estimation in Multi-State Semi-Markov Models (2015) not zbMATH