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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.

• Install and load the spsurv package using the devtools package.

install.packages("devtools")

library(devtools) install_github("rvpanaro/spsurv")

• Check out the main fitter function ??spbp and examples.

library("KMsurv") data("larynx")

library(spsurv)

Maximum Likelihood

fit <- spsurv::spbp(Surv(time, delta)~age+factor(stage), approach = "mle", data = larynx) summary(fit)

NUTS sampling (Bayesian)

fit2 <- spsurv::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.