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