skip_on_os(c("mac", "solaris")) test_that("ggpredict prediction interval, glm", { skip_if_not_installed("glmmTMB") # linear m_pr0 <- lm(barthtot ~ c172code, data = efc) out <- ggpredict(m_pr0, "c172code") expect_equal(out$predicted, c(62.91021, 64.69758, 66.48495), tolerance = 1e-3) expect_equal(out$conf.high, c(66.62681, 66.72464, 70.35304), tolerance = 1e-3) set.seed(123) out <- ggpredict(m_pr0, "c172code", type = "simulate") expect_equal(out$predicted, c(63.00651, 64.68146, 66.43229), tolerance = 1e-3) expect_equal(out$conf.high, c(120.8162, 122.3524, 124.02301), tolerance = 1e-3) out <- ggpredict(m_pr0, "c172code", interval = "prediction") expect_equal(out$predicted, c(62.91021, 64.69758, 66.48495), tolerance = 1e-3) expect_equal(out$conf.high, c(121.12437, 122.82833, 124.70898), tolerance = 1e-3) d <- data_grid(m_pr0, "c172code") out2 <- predict(m_pr0, newdata = d, interval = "prediction") expect_equal(out$conf.high, out2[, 3], tolerance = 1e-3, ignore_attr = TRUE) # poisson data(Salamanders, package = "glmmTMB") m_pr1 <- glm(count ~ mined, family = poisson(link = "log"), data = Salamanders) set.seed(123) out <- ggpredict(m_pr1, "mined", type = "simulate") expect_equal(out$predicted, c(0.2949, 2.26118), tolerance = 1e-3) expect_equal(out$conf.high, c(1.96461, 5.65952), tolerance = 1e-3) out <- ggpredict(m_pr1, "mined") expect_equal(out$predicted, c(0.29545, 2.26488), tolerance = 1e-3) expect_equal(out$conf.high, c(0.36284, 2.43165), tolerance = 1e-3) out <- ggpredict(m_pr1, "mined", interval = "prediction") expect_equal(out$predicted, c(0.29545, 2.26488), tolerance = 1e-3) expect_equal(out$conf.high, c(2, 6), tolerance = 1e-3) # logisitc skip_if(getRversion() < "4.3.0") data(efc, package = "ggeffects") efc$neg_c_7d <- as.numeric(efc$neg_c_7 > median(efc$neg_c_7, na.rm = TRUE)) m_pr2 <- glm(neg_c_7d ~ as.factor(c161sex), data = efc, family = binomial) out <- ggpredict(m_pr2, "c161sex") expect_equal(out$predicted, c(0.34906, 0.47423), tolerance = 1e-3) expect_equal(out$conf.high, c(0.41562, 0.51186), tolerance = 1e-3) out <- ggpredict(m_pr2, "c161sex", interval = "prediction") expect_equal(out$predicted, c(0.34906, 0.47423), tolerance = 1e-3) expect_equal(out$conf.high, c(0.79527, 0.8656), tolerance = 1e-3) })