influence_frailty: Influence Diagnostics for MultiFrailty Models

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

Influence Diagnostics for MultiFrailty Models

Description

Computes leverage (hat values), Cook's distance, DFBETAS, and DFFITS for regression parameters.

Usage

influence_frailty(fit)

Arguments

fit	A fitted object of class "multifrailty_fit".

Value

A list containing leverage, Cook's distance, DFBETAS matrix, DFFITS vector, and a summary diagnostic table.

References

Belsley, D. A., Kuh, E., & Welsch, R. E. (1980). Regression diagnostics: Identifying influential data and sources of collinearity. John Wiley & Sons.

Examples

set.seed(123)
dat <- r_frailty(n = 50, baseline = "weibull", bpar = c(2, 1.5), frailty = "gamma", fpar = c(0.8))
fit <- fit_frailty(time = dat$time, status = dat$status, baseline = "weibull", frailty = "gamma")
inf <- influence_frailty(fit)
head(inf$diagnostics_table)

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