survival::survreg() fits a parametric survival model.
For this engine, there is a single mode: regression
This model has 1 tuning parameters:
dist: Distribution (type: character, default: ‘weibull’)
surv_reg(dist = character(1)) %>%
set_engine("survival") %>%
set_mode("regression") %>%
translate()
## Parametric Survival Regression Model Specification (regression)
##
## Main Arguments:
## dist = character(1)
##
## Computational engine: survival
##
## Model fit template:
## survival::survreg(formula = missing_arg(), data = missing_arg(),
## weights = missing_arg(), dist = character(1), model = TRUE)
Note that model = TRUE is needed to produce quantile predictions when
there is a stratification variable and can be overridden in other cases.
The main interface for this model uses the formula method since the
model specification typically involved the use of
survival::Surv().
The model formula can include special terms, such as
survival::strata(). The allows the model scale
parameter to differ between groups contained in the function. The column
used inside strata() is treated as qualitative no matter its type.
For example, in this model, the numeric column rx is used to estimate
two different scale parameters for each value of the column:
library(survival)surv_reg() %>%
fit(Surv(futime, fustat) ~ age + strata(rx), data = ovarian) %>%
extract_fit_engine()
## Call:
## survival::survreg(formula = Surv(futime, fustat) ~ age + strata(rx),
## data = data, model = TRUE)
##
## Coefficients:
## (Intercept) age
## 12.8734120 -0.1033569
##
## Scale:
## rx=1 rx=2
## 0.7695509 0.4703602
##
## Loglik(model)= -89.4 Loglik(intercept only)= -97.1
## Chisq= 15.36 on 1 degrees of freedom, p= 8.88e-05
## n= 26
Kalbfleisch, J. D. and Prentice, R. L. 2002 The statistical analysis of failure time data, Wiley.