phmm

R package phmm: Proportional Hazards Mixed-effects Model (PHMM). Fits proportional hazards model incorporating random effects using an EM algorithm using Markov Chain Monte Carlo at E-step.

Keywords for this software

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References in zbMATH (referenced in 6 articles )

Showing results 1 to 6 of 6.
Sorted by year (citations)

  1. Theodor Balan; Hein Putter: frailtyEM: An R Package for Estimating Semiparametric Shared Frailty Models (2019) not zbMATH
  2. John Monaco; Malka Gorfine; Li Hsu: General Semiparametric Shared Frailty Model: Estimation and Simulation with frailtySurv (2018) not zbMATH
  3. Ha, Il Do; Jeong, Jong-Hyeon; Lee, Youngjo: Statistical modelling of survival data with random effects. H-likelihood approach (2017)
  4. John V. Monaco, Malka Gorfine, Li Hsu: General Semiparametric Shared Frailty Model Estimation and Simulation with frailtySurv (2017) arXiv
  5. Lee, Youngjo; Ronnegård, Lars; Noh, Maengseok: Data analysis using hierarchical generalized linear models with R (2017)
  6. Marco Munda; Federico Rotolo; Catherine Legrand: parfm: Parametric Frailty Models in R (2012) not zbMATH