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skip_on_cran()
test_that("emmeans | lm", {
skip_if_not_installed("emmeans")
skip_if_not_installed("boot")
skip_if_not_installed("coda")
model <- lm(mpg ~ log(wt) + factor(cyl), data = mtcars)
set.seed(7)
b <- bootstrap_model(model, iterations = 1000)
expect_equal(summary(emmeans::emmeans(b, ~cyl))$emmean,
summary(emmeans::emmeans(model, ~cyl))$emmean,
tolerance = 0.1
)
set.seed(7)
b <- bootstrap_parameters(model, iterations = 1000)
expect_equal(summary(emmeans::emmeans(b, ~cyl))$emmean,
summary(emmeans::emmeans(model, ~cyl))$emmean,
tolerance = 0.1
)
mp <- model_parameters(emmeans::emmeans(b, consec ~ cyl), verbose = FALSE)
expect_identical(
colnames(mp),
c("Parameter", "Median", "CI", "CI_low", "CI_high", "pd", "Component")
)
expect_identical(nrow(mp), 5L)
})
test_that("emmeans | lmer", {
skip_if_not_installed("emmeans")
skip_if_not_installed("boot")
skip_if_not_installed("lme4")
skip_if_not_installed("coda")
model <- lme4::lmer(mpg ~ log(wt) + factor(cyl) + (1 | gear), data = mtcars)
set.seed(7)
b <- bootstrap_model(model, iterations = 1000)
expect_equal(summary(emmeans::emmeans(b, ~cyl))$emmean,
summary(emmeans::emmeans(model, ~cyl))$emmean,
tolerance = 0.1
)
set.seed(7)
b <- bootstrap_parameters(model, iterations = 1000)
expect_equal(summary(emmeans::emmeans(b, ~cyl))$emmean,
summary(emmeans::emmeans(model, ~cyl))$emmean,
tolerance = 0.1
)
mp <- suppressWarnings(model_parameters(emmeans::emmeans(b, consec ~ cyl)))
expect_identical(
colnames(mp),
c("Parameter", "Median", "CI", "CI_low", "CI_high", "pd", "Component")
)
expect_identical(nrow(mp), 5L)
})
test_that("emmeans | glmmTMB", {
skip_if_not_installed("coda")
skip_if_not_installed("emmeans")
skip_if_not_installed("boot")
skip_if_not_installed("lme4")
suppressWarnings(skip_if_not_installed("glmmTMB"))
data(Salamanders, package = "glmmTMB")
model <- glmmTMB::glmmTMB(count ~ spp + mined + (1 | site), family = glmmTMB::nbinom2, data = Salamanders)
set.seed(7)
b <- bootstrap_parameters(model, iterations = 10)
out <- summary(emmeans::emmeans(b, ~spp, type = "response"))
expect_equal(
out$response,
c(0.654, 0.1515, 0.8856, 0.261, 0.9775, 1.2909, 0.9031),
tolerance = 0.1
)
expect_identical(
colnames(out),
c("spp", "response", "lower.HPD", "upper.HPD")
)
expect_identical(nrow(out), 7L)
})
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