library(survival)

# of note, the p-value from lrtest is one-sided pnorm(z), while the p-value
# from survdiff is two-sided 1 - pchisq(z^2, 1)
testthat::test_that("lrtest: two-sided p-value", {
  df1 <- lrtest(ovarian, treat = "rx", time = "futime", event = "fustat")

  df2 <- survdiff(Surv(futime, fustat) ~ rx, data = ovarian)

  testthat::expect_equal(df1$logRankPValue, df2$pvalue)
})


testthat::test_that("lrtest: stratified log-rank test", {
  data1 <- subset(rawdata, iterationNumber == 1)

  df1 <- lrtest(data1, stratum = "stratum", treat = "treatmentGroup",
                time = "timeUnderObservation", event = "event")

  df2 <- survdiff(Surv(timeUnderObservation, event) ~ treatmentGroup +
                    strata(stratum), data = data1)

  testthat::expect_equal(df1$logRankPValue, df2$pvalue)
})


testthat::test_that("lrtest: weighted log-rank test", {
  df1 <- lrtest(aml, treat = "x", time = "time", event = "status", rho1 = 0.5)

  df2 <- survdiff(Surv(time, status) ~ x, rho = 0.5, data = aml)

  testthat::expect_equal(df1$logRankPValue, df2$pvalue)
})