compare_models: Model Comparison, Bootstrapped WAIC, and Cross-Validation for...

In MultiFrailty: Shared Frailty Regression Models with Inverse Gaussian, Generalized Lindley, and Gamma Frailty Distributions

Model Comparison, Bootstrapped WAIC, and Cross-Validation for MultiFrailty Models

Description

Compares multiple fitted shared frailty models using AIC, BIC, AICc, HQIC, optional bootstrapped WAIC, and k-fold cross-validation.

Usage

compare_models(
  ...,
  criteria = c("AIC", "BIC", "AICc", "HQIC"),
  compute_waic = FALSE,
  waic_B = 100L
)

Arguments

...	Fitted "multifrailty_fit" objects passed individually or as a list.
criteria	Character vector of selection criteria to include.
compute_waic	Logical; if TRUE computes bootstrapped WAIC. Default is FALSE.
waic_B	Number of bootstrap samples for WAIC. Default is 100.

Value

A data frame summarizing model comparisons ranked by AIC.

References

Pandey, A., Hanagal, D. D., & Tyagi, S. (2022). Shared Frailty Models Based on Cancer Data. International Journal of Statistics and Reliability Engineering, 9(3), 461-474.

Pandey, A., & Tyagi, S. (2021). Comparison of Multiplicative Frailty Models Under Weibull Baseline Distribution. Lobachevskii Journal of Mathematics, 42(13), 3184-3195.

Examples

set.seed(123)
dat <- r_frailty(n = 60, baseline = "weibull", bpar = c(2, 1.5), frailty = "gamma", fpar = c(0.8))
fit1 <- fit_frailty(time = dat$time, status = dat$status, baseline = "weibull", frailty = "none")
fit2 <- fit_frailty(time = dat$time, status = dat$status, baseline = "weibull", frailty = "gamma")
cmp <- compare_models(fit1, fit2)
print(cmp)

MultiFrailty documentation built on Aug. 8, 2026, 1:07 a.m.