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censored provides engines for survival models from the parsnip package. The models include parametric survival models, proportional hazards models, decision trees, boosted trees, bagged trees, and random forests. See the "Fitting and Predicting with censored" article for various examples. See below for examples of classic survival models and how to fit them with censored.

Author

Maintainer: Hannah Frick hannah@rstudio.com (ORCID)

Authors:

Other contributors:

  • RStudio [copyright holder, funder]

Examples

# Accelerated Failure Time (AFT) model

fit_aft <- survival_reg(dist = "weibull") %>%
  set_engine("survival") %>%
  fit(Surv(time, status) ~ age + sex + ph.karno, data = lung)
predict(fit_aft, lung[1:3, ], type = "time")
#> # A tibble: 3 × 1
#>   .pred_time
#>        <dbl>
#> 1       355.
#> 2       374.
#> 3       416.


# Cox's Proportional Hazards model

fit_cox <- proportional_hazards() %>%
  set_engine("survival") %>%
  fit(Surv(time, status) ~ age + sex + ph.karno, data = lung)
predict(fit_cox, lung[1:3, ], type = "time")
#> # A tibble: 3 × 1
#>   .pred_time
#>        <dbl>
#> 1       325.
#> 2       343.
#> 3       379.


# Andersen-Gill model for recurring events

fit_ag <- proportional_hazards() %>%
  set_engine("survival") %>%
  fit(Surv(tstart, tstop, status) ~ treat + inherit + age + strata(hos.cat),
      data = cgd)
predict(fit_ag, cgd[1:3, ], type = "time")
#> # A tibble: 3 × 1
#>   .pred_time
#>        <dbl>
#> 1       319.
#> 2       319.
#> 3       319.