samp_elife: Simulate excess lifetime with truncation or right-censoring

In longevity: Statistical Methods for the Analysis of Excess Lifetimes

Simulate excess lifetime with truncation or right-censoring

Description

This function dispatches simulations accounting for potential left-truncation (remove by setting lower to zero). If type2=ltrt, simulated observations will be lower than the upper bounds upper. If type2=ltrc, simulated observations are capped at upper and the observation is right-censored (rcens=TRUE).

Usage

samp_elife(
  n,
  scale,
  rate,
  shape = NULL,
  lower = 0,
  upper = Inf,
  family = c("exp", "gp", "gomp", "gompmake", "weibull", "extgp", "gppiece",
    "extweibull", "perks", "beard", "perksmake", "beardmake"),
  type2 = c("none", "ltrt", "ltrc", "ditrunc")
)

Arguments

n	sample size
scale	scale parameter(s)
rate	rate parameter(s)
shape	shape parameter(s)
lower	vector of lower bounds
upper	vector of upper bounds
family	string; choice of parametric family
type2	string, either none, ltrt for left- and right-truncated data or ltrc for left-truncated right-censored data

Value

either a vector of observations or, if type2=ltrc, a list with n observations dat and a logical vector of the same length with TRUE for right-censored observations and FALSE otherwise.

Note

As the tails of the Gompertz and Gompertz–Makeham models decrease exponentially fast, the method fails in the rare event case if the lower bound is too large (say larger than the 99.99

Examples

set.seed(1234)
n <- 500L
# Simulate interval truncated data
x <- samp_elife(n = n,
                scale = 2,
                shape = 1.5,
                lower = low <- runif(n),
                upper = upp <- runif(n, min = 3, max = 15),
                type2 = "ltrt",
                family = "weibull")
coef(fit_elife(
   time = x,
   ltrunc = low,
   rtrunc = upp,
   family = "weibull"))
# Simulate left-truncated right-censored data
x <- samp_elife(n = n,
                scale = 2,
                shape = 1.5,
                lower = low <- runif(n),
                upper = upp <- runif(n, min = 3, max = 15),
                type2 = "ltrc",
                family = "gomp")
#note that the return value is a list...
coef(fit_elife(
   time = x$dat,
   ltrunc = low,
   event = !x$rcens,
   family = "gomp"))

longevity documentation built on June 8, 2025, 10:31 a.m.