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

# \donttest{
library(survstan)
library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union

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")
)
#> Warning: There was 1 warning in `dplyr::mutate()`.
#> ℹ In argument: `fit = purrr::pmap(...)`.
#> Caused by warning in `ahreg()`:
#> ! The AH model with baseline exponential distribution is non-identifiable! Please, choose another baseline distribution.
# }