test_that('glmer execution', {
skip_if_not_installed("lme4")
skip_on_cran()
glmer_cl <- call2("glmer", .ns = "lme4", f, data = expr(riesby_tr), family = gaussian(make.link("identity")))
set.seed(2452)
glmer_mod <- eval_tidy(glmer_cl)
set.seed(2452)
expect_error(
ps_mod <-
linear_reg() %>%
set_engine("glmer", family = gaussian(make.link("identity"))) %>%
fit(f, data = riesby_tr),
regex = NA
)
expect_equal(
coef(ps_mod$fit)$subject,
coef(glmer_mod)$subject
)
glmer_pred <- predict(glmer_mod, riesby_te, allow.new.levels = TRUE)
ps_pred <- predict(ps_mod, riesby_te)
expect_equal(unname(glmer_pred), ps_pred$.pred)
})
test_that('mode specific package dependencies', {
expect_identical(
get_from_env(paste0("linear_reg", "_pkgs")) %>%
dplyr::filter(engine == "glmer", mode == "classification") %>%
dplyr::pull(pkg),
list()
)
expect_identical(
get_from_env(paste0("linear_reg", "_pkgs")) %>%
dplyr::filter(engine == "glmer", mode == "regression") %>%
dplyr::pull(pkg),
list(c("lme4", "multilevelmod"))
)
})
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