skip_if_not_installed("rms")
skip_if_not_installed("survival")
Surv <- survival::Surv
pol <- rms::pol
n <- 400
set.seed(1)
age <- rnorm(n, 50, 12)
sex <- factor(sample(c("Female", "Male"), n, TRUE))
# Population hazard function:
h <- 0.02 * exp(0.06 * (age - 50) + 0.8 * (sex == "Female"))
d.time <- -log(runif(n)) / h
cens <- 15 * runif(n)
death <- as.integer(d.time <= cens)
d.time <- pmin(d.time, cens)
dat <<- data.frame(d.time, death, sex, age, stringsAsFactors = FALSE)
m1 <- rms::psm(Surv(d.time, death) ~ sex * pol(age, 2),
dist = "lognormal",
data = dat
)
test_that("model_info", {
expect_false(model_info(m1)$is_binomial)
expect_false(model_info(m1)$is_logit)
})
test_that("find_predictors", {
expect_identical(find_predictors(m1), list(conditional = c("sex", "age")))
expect_identical(find_predictors(m1, flatten = TRUE), c("sex", "age"))
expect_null(find_predictors(m1, effects = "random"))
})
test_that("find_random", {
expect_null(find_random(m1))
})
test_that("get_random", {
expect_warning(get_random(m1))
})
test_that("find_response", {
expect_identical(find_response(m1), "Surv(d.time, death)")
expect_identical(find_response(m1, combine = FALSE), c("d.time", "death"))
})
test_that("get_response", {
expect_equal(get_response(m1), dat[, c("d.time", "death")])
})
test_that("get_predictors", {
expect_equal(colnames(get_predictors(m1)), c("sex", "age"))
})
test_that("link_inverse", {
expect_equal(link_inverse(m1)(0.2), exp(0.2), tolerance = 1e-5)
})
test_that("get_data", {
expect_equal(nrow(get_data(m1)), 400)
expect_equal(colnames(get_data(m1)), c("d.time", "death", "sex", "age"))
})
test_that("find_formula", {
expect_length(find_formula(m1), 1)
expect_equal(
find_formula(m1),
list(conditional = as.formula(
"Surv(d.time, death) ~ sex * pol(age, 2)"
)),
ignore_attr = TRUE
)
})
test_that("find_terms", {
expect_length(find_terms(m1), 2)
expect_equal(
find_terms(m1),
list(
response = "Surv(d.time, death)",
conditional = c("sex", "pol(age, 2)")
)
)
})
test_that("find_variables", {
expect_equal(find_variables(m1), list(
response = c("d.time", "death"),
conditional = c("sex", "age")
))
expect_equal(
find_variables(m1, flatten = TRUE),
c("d.time", "death", "sex", "age")
)
})
test_that("n_obs", {
expect_equal(n_obs(m1), 400)
})
test_that("linkfun", {
expect_false(is.null(link_function(m1)))
})
test_that("linkinverse", {
expect_false(is.null(link_inverse(m1)))
})
test_that("find_parameters", {
expect_equal(
find_parameters(m1),
list(
conditional = c(
"(Intercept)",
"sex=Male",
"age",
"age^2",
"sex=Male * age",
"sex=Male * age^2"
)
)
)
expect_equal(nrow(get_parameters(m1)), 6)
expect_equal(
get_parameters(m1)$Parameter,
c(
"(Intercept)",
"sex=Male",
"age",
"age^2",
"sex=Male * age",
"sex=Male * age^2"
)
)
})
test_that("is_multivariate", {
expect_false(is_multivariate(m1))
})
test_that("find_algorithm", {
expect_warning(find_algorithm(m1))
})
test_that("find_statistic", {
expect_identical(find_statistic(m1), "z-statistic")
})
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