Description Engine Details References See Also
These are engines for the parsnip::survival_reg()
model specification.
survival_reg()
is a way to generate a specification of a model
before fitting and allows the model to be created using
R. The main argument for the
model is:
dist
: The probability distribution of the outcome.
This argument is converted to its specific names at the
time that the model is fit. Other options and argument can be
set using set_engine()
. If left to its default
here (NULL
), the value is taken from the underlying model
functions.
Since survival models typically involve censoring (and require the use of
survival::Surv()
objects), the fit()
function will require that the
survival model be specified via the formula interface.
Also, for the flexsurv::flexsurvfit
engine, the typical
strata
function cannot be used. To achieve the same effect,
the extra parameter roles can be used (as described above).
The model can be created using the fit()
function using the
following engines:
R: "flexsurv"
, "survival"
(the default)
Engines may have preset default arguments when executing the model fit call. For this type of model, the template of the fit calls are below.
survival_reg() %>% set_engine("flexsurv") %>% set_mode("censored regression") %>% translate()
1 2 3 4 5 6 7  ## Parametric Survival Regression Model Specification (censored regression)
##
## Computational engine: flexsurv
##
## Model fit template:
## flexsurv::flexsurvreg(formula = missing_arg(), data = missing_arg(),
## weights = missing_arg())

survival_reg() %>% set_engine("survival") %>% set_mode("censored regression") %>% translate()
1 2 3 4 5 6 7  ## Parametric Survival Regression Model Specification (censored regression)
##
## Computational engine: survival
##
## Model fit template:
## survival::survreg(formula = missing_arg(), data = missing_arg(),
## weights = missing_arg(), 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.
fit()
passes the data directly to survival::curvreg()
so that its
formula method can create dummy variables asneeded.
The standardized parameter names in parsnip can be mapped to their original names in each engine that has main parameters. Each engine typically has a different default value (shown in parentheses) for each parameter.
parsnip  survival  flexsurv 
dist  dist  dist 
Jackson, C. (2016). flexsurv
: A Platform for Parametric Survival
Modeling in R. Journal of Statistical Software, 70(8), 1  33.
parsnip::survival_reg()
, parsnip::fit()
, survival::Surv()
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