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survregVB
is an R package that provides Bayesian inference for log-logistic accelerated failure time (AFT) models used in survival analysis as a faster alternative to Markov chain Monte Carlo (MCMC) methods. The details of the Variational Bayes algorithms with and without shared frailty can be found in Xian et al., (2024a) and Xian et al., (2024b) respectively.
To install survregVB
, use the following command:
remotes::install_github("https://github.com/chengqianxian/survregVB")
library(survregVB)
library(survival)
# Example using dataset included in the package
data(dnase)
# Fit a survival model
fit <- survregVB(formula = Surv(time, infect) ~ trt + fev, data = dnase,
alpha_0 = 501, omega_0 = 500, mu_0 = c(4.4, 0.25, 0.04), v_0 = 1)
# Print summary
summary(fit)
# Using dataset included in the package
data(simulation_frailty)
# Fit a survival model with shared frailty
fit_frailty <- survregVB(formula = Surv(Time.15, delta.15) ~ x1 + x2, data = simulation_frailty,
alpha_0 = 3, omega_0 = 2, mu_0 = c(0, 0, 0), v_0 = 0.1,
lambda_0 = 3, eta_0 = 2, cluster = cluster)
# Print summary
summary(fit_frailty)
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