samp_elife {longevity}

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"))