tests/testthat/test-absRiskComp.R

# Handling warning messages coming from montecarlo integration
handler_validmc <- function(msg) {
    if (any(grepl("out of range", msg))) invokeRestart("muffleWarning")
}

# To pass the noLD checks
eps <- if (capabilities("long.double"))
    sqrt(.Machine$double.eps) else
        0.1

n <- 100
alp <- 0.05
lambda10 <- 1
lambda20 <- 2
lambda11 <- 4
lambda21 <- 5

lambda_t0 <- lambda10 + lambda20
lambda_t1 <- lambda11 + lambda21

times <- c(rexp(n = n, rate = lambda_t0),
           rexp(n = n, rate = lambda_t1))
event <- c(rbinom(n, 1, prob = lambda10 / lambda_t0),
           rbinom(n, 1, prob = lambda11 / lambda_t1)) + 1
censor <- rexp(n = 2 * n, rate = -log(alp))

times_c <- pmin(times, censor)
event_c <- event * (times < censor)

DT <- data.table("ftime" = times_c,
                 "event" = event_c,
                 "Z" = c(rep(0, n),
                         rep(1, n)))

DF <- data.frame("ftime" = times_c,
                 "event" = event_c,
                 "Z" = c(rep(0, n), rep(1, n)))

fitDF <- fitSmoothHazard(event ~ Z, data = DF, time = "ftime")
fitDT <- fitSmoothHazard(event ~ Z, data = DT, time = "ftime")

test_that("no error in absolute risk with data frames", {
    foo1 <- try(withCallingHandlers(absoluteRisk(fitDF, time = 1,
                                                 newdata = DF[1, ],
                             method = "montecarlo", nsamp = 10),
                             warning = handler_validmc),
                silent = TRUE)
    foo2 <- try(absoluteRisk(fitDF, time = 1, newdata = DF[1, ],
                             method = "numerical"),
                silent = TRUE)

    expect_false(inherits(foo1, "try-error"))
    expect_false(inherits(foo2, "try-error"))
})

test_that("no error in absolute risk with data tables", {
    foo1 <- try(withCallingHandlers(absoluteRisk(fitDT, time = 1,
                                                 newdata = DT[1, ],
                             method = "montecarlo", nsamp = 10),
                             warning = handler_validmc),
                silent = TRUE)
    foo2 <- try(absoluteRisk(fitDT, time = 1, newdata = DT[1, ],
                             method = "numerical"),
                silent = TRUE)

    expect_false(inherits(foo1, "try-error"))
    expect_false(inherits(foo2, "try-error"))
})

# Using new data
newDT <- data.table("Z" = c(0, 1))
newDF <- data.frame("Z" = c(0, 1))

test_that("no error in absolute risk with data frames - new data", {
    foo1 <- try(withCallingHandlers(absoluteRisk(fitDF, time = 1,
                                                 newdata = newDF,
                             method = "montecarlo", nsamp = 10),
                             warning = handler_validmc),
                silent = TRUE)
    foo2 <- try(absoluteRisk(fitDF, time = 1, newdata = newDF,
                             method = "numerical"),
                silent = TRUE)

    expect_false(inherits(foo1, "try-error"))
    expect_false(inherits(foo2, "try-error"))
})

test_that("no error in absolute risk with data tables - new data", {
    foo1 <- try(withCallingHandlers(absoluteRisk(fitDT, time = 1,
                                                 newdata = newDT,
                             method = "montecarlo", nsamp = 10),
                             warning = handler_validmc),
                silent = TRUE)
    foo2 <- try(absoluteRisk(fitDT, time = 1, newdata = newDT,
                             method = "numerical"),
                silent = TRUE)

    expect_false(inherits(foo1, "try-error"))
    expect_false(inherits(foo2, "try-error"))
})

# Make sure we get probabilities
test_that("should output probabilities with data frames", {
    absRiskMC <- absoluteRisk(fitDF, time = 1, newdata = DF[1, ],
                              method = "montecarlo")
    absRiskNI <- absoluteRisk(fitDF, time = 1, newdata = DF[1, ],
                              method = "numerical")

    expect_true(all(absRiskMC[, -1] >= 0 - eps))
    expect_true(all(absRiskNI[, -1] >= 0 - eps))
    expect_true(all(absRiskMC[, -1] <= 1 + eps))
    expect_true(all(absRiskNI[, -1] <= 1 + eps))
})

test_that("should output probabilities with data tables", {
    absRiskMC <- absoluteRisk(fitDT, time = 1, newdata = DT[1, ],
                              method = "montecarlo")
    absRiskNI <- absoluteRisk(fitDT, time = 1, newdata = DT[1, ],
                              method = "numerical")

    expect_true(all(absRiskMC[, -1] >= 0 - eps))
    expect_true(all(absRiskNI[, -1] >= 0 - eps))
    expect_true(all(absRiskMC[, -1] <= 1 + eps))
    expect_true(all(absRiskNI[, -1] <= 1 + eps))
})

test_that("should output probabilities with data frames - two time points", {
    absRiskMC <- absoluteRisk(fitDF, time = c(0.5, 1), newdata = DF[1, ],
                              method = "montecarlo")
    absRiskNI <- absoluteRisk(fitDF, time = c(0.5, 1), newdata = DF[1, ],
                              method = "numerical")

    expect_true(all(absRiskMC[, -1] >= 0 - eps))
    expect_true(all(absRiskNI[, -1] >= 0 - eps))
    expect_true(all(absRiskMC[, -1] <= 1 + eps))
    expect_true(all(absRiskNI[, -1] <= 1 + eps))
})

test_that("should output probabilities with data tables - two time points", {
    absRiskMC <- absoluteRisk(fitDT, time = c(0.5, 1), newdata = DT[1, ],
                              method = "montecarlo")
    absRiskNI <- absoluteRisk(fitDT, time = c(0.5, 1), newdata = DT[1, ],
                              method = "numerical")

    expect_true(all(absRiskMC[, -1] >= 0 - eps))
    expect_true(all(absRiskNI[, -1] >= 0 - eps))
    expect_true(all(absRiskMC[, -1] <= 1 + eps))
    expect_true(all(absRiskNI[, -1] <= 1 + eps))
})

test_that(paste("should output probabilities with data frames",
                "- two covariate profile"), {
    absRiskMC <- absoluteRisk(fitDF, time = 1, newdata = DF[c(1, n + 1), ],
                              method = "montecarlo")
    absRiskNI <- absoluteRisk(fitDF, time = 1, newdata = DF[c(1, n + 1), ],
                              method = "numerical")

    expect_true(all(absRiskMC >= 0 - eps))
    expect_true(all(absRiskNI >= 0 - eps))
    expect_true(all(absRiskMC <= 1 + eps))
    expect_true(all(absRiskNI <= 1 + eps))
})

test_that(paste("should output probabilities with data tables",
                "- two covariate profile"), {
    absRiskMC <- absoluteRisk(fitDT, time = 1, newdata = DT[c(1, n + 1), ],
                              method = "montecarlo")
    absRiskNI <- absoluteRisk(fitDT, time = 1, newdata = DT[c(1, n + 1), ],
                              method = "numerical")

    expect_true(all(absRiskMC >= 0 - eps))
    expect_true(all(absRiskNI >= 0 - eps))
    expect_true(all(absRiskMC <= 1 + eps))
    expect_true(all(absRiskNI <= 1 + eps))
})

test_that("no error in absolute risk with type survival", {
    foo1 <- try(withCallingHandlers(absoluteRisk(fitDF, time = 1,
                                                 newdata = newDF,
                                                 method = "montecarlo",
                                                 type = "survival"),
                                    warning = handler_validmc),
                silent = TRUE)
    foo2 <- try(absoluteRisk(fitDF, time = 1, newdata = newDF,
                             method = "numerical", type = "survival"),
                silent = TRUE)
    foo3 <- try(withCallingHandlers(absoluteRisk(fitDT, time = 1,
                                                 newdata = newDT,
                                                 method = "montecarlo",
                                                 type = "survival"),
                                    warning = handler_validmc),
                silent = TRUE)
    foo4 <- try(absoluteRisk(fitDT, time = 1, newdata = newDT,
                             method = "numerical", type = "survival"),
                silent = TRUE)

    expect_false(inherits(foo1, "try-error"))
    expect_false(inherits(foo2, "try-error"))
    expect_false(inherits(foo3, "try-error"))
    expect_false(inherits(foo4, "try-error"))
})

Try the casebase package in your browser

Any scripts or data that you put into this service are public.

casebase documentation built on Nov. 16, 2022, 5:11 p.m.