rank_models: Rank a collection of survstan models

In survstan: Fitting Survival Regression Models via 'Stan'

Rank a collection of survstan models

Description

Rank a collection of survstan models

Usage

rank_models(formula, data, survreg, baseline, dist = NULL, ...)

Arguments

formula	an object of class "formula" (or one that can be coerced to that class): a symbolic description of the model to be fitted.
data	data an optional data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model. If not found in data, the variables are taken from environment(formula), typically the environment from which function is called.
survreg	survival regression models to be fitted (AFT, AH, PH, PO, YP and EH).
baseline	baseline distributions to be fitted; options currently available are: exponential, weibull, lognormal, loglogistic and Birnbaum-Saunders (fatigue) distributions.
dist	alternative way to specify the baseline distributions (for compability with the survreg function); default is NULL.
...	further arguments passed to other methods.

Value

a tibble containing the fitted models ranked according to their AICs.

Examples

library(survstan)
library(dplyr)

veteran <- veteran %>%
  mutate(across(c(trt, prior, celltype), as.factor))
fits <- rank_models(
  formula = Surv(time, status) ~ celltype+karno,
  data = veteran,
  survreg = c("aftreg", "ahreg", "phreg", "poreg", "ypreg", "ehreg"),
  baseline = c("exponential", "weibull", "lognormal", "loglogistic", "fatigue", "gamma", "rayleigh")
)

survstan documentation built on May 29, 2024, 8:41 a.m.