Nothing
skip_on_cran()
skip_if_not(broom.helpers::.assert_package("car", pkg_search = "gtsummary", boolean = TRUE))
mod <- lm(age ~ marker + grade, trial)
test_that("no errors/warnings with tidy_standardize", {
skip_if_not(broom.helpers::.assert_package("effectsize", pkg_search = "gtsummary", boolean = TRUE))
expect_snapshot(tbl_regression(mod, tidy_fun = tidy_standardize) %>% as.data.frame())
})
test_that("no errors/warnings with tidy_bootstrap", {
skip_if_not(broom.helpers::.assert_package("parameters", pkg_search = "gtsummary", boolean = TRUE))
skip_if_not_installed("boot")
set.seed(123)
expect_warning(tbl_regression(mod, tidy_fun = tidy_bootstrap), NA)
skip_on_os(c("windows", "linux", "solaris"))
expect_snapshot(tbl_regression(mod, tidy_fun = tidy_bootstrap) %>% as.data.frame())
})
test_that("no errors/warnings with pool_and_tidy_mice", {
skip_if_not(broom.helpers::.assert_package("mice", pkg_search = "gtsummary", boolean = TRUE))
mod_mice <-
suppressWarnings(mice::mice(trial, m = 2, seed = 123)) %>%
with(glm(response ~ age + marker + grade, family = binomial))
expect_error(mice::pool(mod_mice) %>% tbl_regression(), NA)
expect_output(mice::pool(mod_mice), NA)
skip_on_os(c("windows", "linux", "solaris"))
tbl_mice <- tbl_regression(mod_mice)
expect_snapshot(tbl_mice %>% as.data.frame())
})
test_that("no errors/warnings with tbl_regression.multinom", {
skip_if_not(broom.helpers::.assert_package("nnet", pkg_search = "gtsummary", boolean = TRUE))
skip_on_os(c("windows", "linux", "solaris"))
expect_output(
tbl_nnet <-
nnet::multinom(grade ~ age, trial) %>%
tbl_regression(estimate_fun = function(x) style_sigfig(x, digits = 1))
)
expect_snapshot(tbl_nnet %>% as.data.frame())
expect_snapshot(tbl_nnet %>% as_tibble())
})
test_that("no errors/warnings with tbl_regression.gam", {
skip_if_not(broom.helpers::.assert_package("mgcv", pkg_search = "gtsummary", boolean = TRUE))
mod <- mgcv::gam(response ~ s(marker, age) + grade, data = trial, family = binomial)
expect_snapshot(mod %>% tidy_gam())
# test the exp argument is working
expect_equal(
mod %>% tidy_gam(exponentiate = TRUE, conf.int = TRUE),
mod %>%
tidy_gam(exponentiate = FALSE, conf.int = TRUE) %>%
dplyr::mutate_at(vars(any_of(c("estimate", "conf.low", "conf.high"))), exp)
)
expect_snapshot(
mod %>%
tbl_regression(
exponentiate = TRUE,
label = `s(marker,age)` ~ "Smoothed marker/age"
) %>%
as.data.frame()
)
})
test_that("no errors/warnings with tidy_robust()", {
skip_if_not(broom.helpers::.assert_package("parameters", pkg_search = "gtsummary", boolean = TRUE))
skip_if_not(broom.helpers::.assert_package("insight", pkg_search = "gtsummary", boolean = TRUE))
expect_snapshot(
glm(response ~ age + trt, trial, family = binomial) %>%
tbl_regression(
tidy_fun = purrr::partial(tidy_robust, vcov_estimation = "CL"),
exponentiate = TRUE
) %>%
as.data.frame()
)
# expect message when `vcov` and `vcov_args` have not been specified
expect_snapshot(
glm(response ~ age + trt, trial, family = binomial) %>% tidy_robust()
)
})
test_that("no errors/warnings with tidy_wald_test()", {
skip_if_not(broom.helpers::.assert_package("aod", pkg_search = "gtsummary", boolean = TRUE))
mod <- lm(age ~ stage + marker, trial)
# why is the statistic different stage!?
expect_equal(
tidy_wald_test(mod) %>%
dplyr::select(term, df, p.value),
car::Anova(mod, type = 3) %>%
broom::tidy() %>%
dplyr::slice_head(n = 3) %>%
dplyr::select(term, df, p.value),
tolerance = 10e-2,
ignore_attr = TRUE
)
})
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