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) })