Random generation from accelerated failure time models

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

Usage

raftreg(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 = raftreg(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> 0.69639390, 1.60853414, 2.23836513, -1.11901717, 0.64653626, -0…
#> $ sex    <chr> "m", "m", "f", "f", "m", "f", "m", "m", "f", "f", "m", "f", "f"…
#> $ t      <dbl> 12.73057373, 19.08638479, 2.07901391, 0.24776016, 2.46264134, 0…
#> $ c      <dbl> 7.2301897, 7.1553368, 1.5846726, 0.2583867, 0.2120974, 3.886833…
#> $ time   <dbl> 7.23018967, 7.15533683, 1.58467257, 0.24776016, 0.21209739, 0.8…
#> $ status <dbl> 0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, …