Random generation from accelerated hazard models

Function to generate a random sample of survival data from accelerated hazard models.

Usage

rahreg(u, formula, baseline, beta, dist = NULL, package = NULL, data, ...)

Arguments

u: a numeric vector of quantiles.
formula: formula specifying the linear predictors.
baseline: the name of the baseline survival distribution.
beta: vector of regression coefficients.
dist: an alternative way to specify the baseline survival distribution.
package: the name of the package where the assumed quantile function is implemented.
data: data frame containing the covariates used to generate the survival times.
...: further arguments passed to other methods.

Value

a numeric vector containing the generated random sample.

Examples

library(rsurv)
library(dplyr)
n <-  1000
simdata <- data.frame(
  age = rnorm(n),
  sex = sample(c("f", "m"), size = n, replace = TRUE)
) %>%
  mutate(
    t = rahreg(runif(n), ~ age+sex, beta = c(1, 2),
                dist = "weibull", shape = 1.5, scale = 1),
    c = runif(n, 0, 10)
  ) %>%
  rowwise() %>%
  mutate(
    time = min(t, c),
    status = as.numeric(time == t)
  )
glimpse(simdata)
#> Rows: 1,000
#> Columns: 6
#> Rowwise: 
#> $ age    <dbl> -0.07957744, -0.37283157, 1.29217027, 0.24680683, -1.71876166, …
#> $ sex    <chr> "m", "f", "m", "m", "m", "f", "m", "f", "m", "f", "m", "m", "m"…
#> $ t      <dbl> 4.7724909, 0.3177694, 4.2323675, 3.1660868, 0.4123813, 0.161969…
#> $ c      <dbl> 6.3434063, 7.7024087, 9.1999357, 9.7401338, 6.3918558, 6.085308…
#> $ time   <dbl> 4.7724909, 0.3177694, 4.2323675, 3.1660868, 0.4123813, 0.161969…
#> $ status <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, …