model_fit_measures: Goodness of fit information for survival-survival model

In Surrogate: Evaluation of Surrogate Endpoints in Clinical Trials

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 fit_model_SurvSurv().

Details

The following goodness-of-fit measures are returned in a named vector:

• tau_0 and tau_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)

Surrogate documentation built on June 22, 2024, 9:16 a.m.