tests/testthat/test-quick_surv.R

In crosstable: Crosstables for Descriptive Analyses

test_that("survival POC", {

  # mtcars3 %>%
  #   transmute(time=as.numeric(disp), event=as.numeric(factor(am))-1,
  #             group=ifelse(is.na(dummy2), "A", "B")) %>%
  #   arrange(time) %>% as.data.frame() %>%
  #   # filter(time<150) %>%
  #   constructive::construct()

  expect_snapshot({

    df = data.frame(
      time = c(71.1, 75.7, 78.7, 79, 95.1, 108, 120.1, 120.3, 121, 140.8, 145, 146.7, 160,
               160, 167.6, 167.6, 225, 258, 275.8, 275.8, 275.8, 301, 304, 318, 350, 351,
               360, 360, 400, 440, 460, 472),
      event = rep(rep(c(1, 0), 6), c(6L, 1L, 2L, 1L, 1L, 1L, 2L, 7L, 1L, 3L, 1L, 6L)),
      group = rep(c("B", "A", "B", "A", "B", "A", "B", "A", "B", "A", "B"),
                  c(9L, 1L, 1L, 1L, 2L, 3L, 1L, 1L, 7L, 2L, 4L))
    )
    df$time = round(df$time)
    df$surv = survival::Surv(df$time, df$event)
    fit = survival::survfit(surv~group, data=df)
    times = sort(unique(fit$time))
    x = summary(fit, times=times, extend=TRUE)
    a = data.frame(strata=x$strata, time=x$time, n.risk=x$n.risk, n.event=x$n.event, surv=x$surv)

    a %>%
      dplyr::filter(strata=="group=B") %>%
      dplyr::filter(time==141)
  })


  #t=140.8
  #on local 4.3 : 1/15
  #on local 4.4 : 1/15
  #on ubuntu-devel : 1/15
  #on 4.4.1 : 0/15
  #on release : 0/15

})


# library(tidyverse)
# df = data.frame(
#   time = c(71.1, 75.7, 78.7, 79, 95.1, 108, 120.1, 120.3, 121, 140.8, 145, 146.7, 160,
#            160, 167.6, 167.6, 225, 258, 275.8, 275.8, 275.8, 301, 304, 318, 350, 351,
#            360, 360, 400, 440, 460, 472),
#   event = rep(rep(c(1, 0), 6), c(6L, 1L, 2L, 1L, 1L, 1L, 2L, 7L, 1L, 3L, 1L, 6L)),
#   group = rep(c("B", "A", "B", "A", "B", "A", "B", "A", "B", "A", "B"),
#               c(9L, 1L, 1L, 1L, 2L, 3L, 1L, 1L, 7L, 2L, 4L))
# )
# df$time = round(df$time)
# df$surv = survival::Surv(df$time, df$event)
# fit = survival::survfit(surv~group, data=df)
# times = sort(fit$time)
#
# x = summary(fit, times=times, extend=TRUE)
# a = data.frame(strata=x$strata, time=x$time, n.risk=x$n.risk, n.event=x$n.event, surv=x$surv)
#
# a %>%
#   dplyr::filter(strata=="group=B") %>%
#   dplyr::filter(time==141)
#
# df %>%
#   dplyr::filter(time==141)
#
# packageVersion("survival")
# R.version.string
#
# reprex::reprex()