An R package for semi-parametric survival analysis.
The spsurv package was designed to contribute with a flexible set of semi-parametric survival regression modelings, including proportional hazards (PH), proportional odds (PO), and accelerated failure time (AFT) models for right-censored data.
library("KMsurv")
data("larynx")
library(spsurv)
## Maximum Likelihood
fit <- spbp(Surv(time, delta)~age+factor(stage),
approach = "mle", data = larynx)
summary(fit)
## NUTS sampling (Bayesian)
fit2 <- spbp(Surv(time, delta)~age+factor(stage),
approach = "bayes", data = larynx,
iter = 2000, chains = 1, warmup = 1000)
summary(fit2)
The spsurv already provides: - Integration with Stan software. - Estimates either in Bayesian or Frequentist (point estimate) inferential approaches. - Three survival regression classes: PH, PO and AFT. - Six distinct prior specifications in a Bayesian analysis.