model_fit_measures {Surrogate} | R Documentation |
Goodness of fit information for survival-survival model
Description
This function returns several goodness-of-fit measures for a model fitted by
fit_model_SurvSurv()
. These are primarily intended for model selection.
Usage
model_fit_measures(fitted_model)
Arguments
fitted_model |
returned value from |
Details
The following goodness-of-fit measures are returned in a named vector:
-
tau_0
andtau_1
: (latent) value for Kendall's tau in the estimated model. -
log_lik
: the maximized log-likelihood value. -
AIC
: the Aikaike information criterion of the fitted model.
Value
a named vector containing the goodness-of-fit measures
Examples
library(Surrogate)
data("Ovarian")
#For simplicity, data is not recoded to semi-competing risks format, but is
#left in the composite event format.
data = data.frame(
Ovarian$Pfs,
Ovarian$Surv,
Ovarian$Treat,
Ovarian$PfsInd,
Ovarian$SurvInd
)
ovarian_fitted =
fit_model_SurvSurv(data = data,
copula_family = "clayton",
n_knots = 1)
model_fit_measures(ovarian_fitted)
[Package Surrogate version 3.3.0 Index]