details_survival_reg_survival: Parametric survival regression

In parsnip: A Common API to Modeling and Analysis Functions

Parametric survival regression

Description

survival::survreg() fits a parametric survival model.

Details

For this engine, there is a single mode: censored regression

Tuning Parameters

This model has 1 tuning parameters:

• dist: Distribution (type: character, default: ‘weibull’)

Translation from parsnip to the original package

The censored extension package is required to fit this model.

library(censored)

survival_reg(dist = character(1)) %>% 
  set_engine("survival") %>% 
  set_mode("censored regression") %>% 
  translate()

## Parametric Survival Regression Model Specification (censored 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)

Other details

In the translated syntax above, 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)

survival_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

Predictions of type "time" are predictions of the mean survival time.

Case weights

This model can utilize case weights during model fitting. To use them, see the documentation in case_weights and the examples on tidymodels.org.

The fit() and fit_xy() arguments have arguments called case_weights that expect vectors of case weights.

Saving fitted model objects

This model object contains data that are not required to make predictions. When saving the model for the purpose of prediction, the size of the saved object might be substantially reduced by using functions from the butcher package.

References

• Kalbfleisch, J. D. and Prentice, R. L. 2002 The statistical analysis of failure time data, Wiley.

parsnip documentation built on Aug. 18, 2023, 1:07 a.m.