skip_on_os(c("mac", "solaris"))
skip_if_not_installed("datawizard")
skip_if_not_installed("withr")
test_that("ggpredict, condition", {
data(efc, package = "ggeffects")
efc$e42dep <- datawizard::to_factor(efc$e42dep)
fit <- lm(barthtot ~ c12hour + neg_c_7 + e42dep + c172code, data = efc)
expect_s3_class(ggpredict(fit, "c172code"), "data.frame")
expect_s3_class(ggpredict(fit, "c172code", condition = c(c12hour = 40)), "data.frame")
expect_s3_class(ggpredict(fit, "c172code", condition = c(c12hour = 40, e42dep = "severely dependent")), "data.frame")
expect_s3_class(ggpredict(fit, "c172code", condition = c(e42dep = "severely dependent")), "data.frame")
dg <- data_grid(fit, "c172code", condition = c(c12hour = 40, e42dep = "severely dependent"))
out1 <- ggpredict(fit, "c172code", condition = c(c12hour = 40, e42dep = "severely dependent"))
out2 <- predict(fit, newdata = dg)
expect_equal(out1$predicted, out2, tolerance = 1e-4, ignore_attr = TRUE)
dg <- data_grid(fit, "c172code")
out1 <- ggpredict(fit, "c172code")
out2 <- predict(fit, newdata = dg)
expect_equal(out1$predicted, out2, tolerance = 1e-4, ignore_attr = TRUE)
skip_if_not_installed("emmeans")
expect_s3_class(ggemmeans(fit, "c172code"), "data.frame")
expect_s3_class(ggemmeans(fit, "c172code", condition = c(c12hour = 40)), "data.frame")
expect_s3_class(ggemmeans(fit, "c172code", condition = c(c12hour = 40, e42dep = "severely dependent")), "data.frame")
expect_s3_class(ggemmeans(fit, "c172code", condition = c(e42dep = "severely dependent")), "data.frame")
})
withr::with_environment(
new.env(),
test_that("ggpredict, condition, glm", {
skip_if_not_installed("emmeans")
data(efc, package = "ggeffects")
efc$e42dep <- datawizard::to_factor(efc$e42dep)
efc$neg_c_7d <- as.numeric(efc$neg_c_7 > median(efc$neg_c_7, na.rm = TRUE))
d <- efc
m1 <- glm(
neg_c_7d ~ c12hour + e42dep + c161sex + c172code,
data = d,
family = binomial(link = "logit")
)
expect_s3_class(
ggpredict(m1, "c12hour", condition = c(e42dep = "severely dependent"), verbose = FALSE),
"data.frame"
)
expect_s3_class(
ggpredict(m1, c("c12hour", "c161sex"), condition = c(e42dep = "severely dependent"), verbose = FALSE),
"data.frame"
)
expect_s3_class(
ggpredict(m1, c("c12hour", "c161sex", "c172code"), condition = c(e42dep = "severely dependent"), verbose = FALSE),
"data.frame"
)
expect_s3_class(
ggemmeans(m1, "c12hour", condition = c(e42dep = "severely dependent"), verbose = FALSE),
"data.frame"
)
expect_s3_class(
ggemmeans(m1, c("c12hour", "c161sex"), condition = c(e42dep = "severely dependent"), verbose = FALSE),
"data.frame"
)
expect_s3_class(
ggemmeans(m1, c("c12hour", "c161sex", "c172code"), condition = c(e42dep = "severely dependent"), verbose = FALSE),
"data.frame"
)
out <- ggpredict(m1, "c172code", condition = c(e42dep = "severely dependent"), verbose = FALSE)
expect_equal(out$predicted, c(0.60806, 0.64322, 0.67691), tolerance = 1e-3)
out <- ggpredict(m1, "c172code", condition = c(e42dep = "independent"), verbose = FALSE)
expect_equal(out$predicted, c(0.10815, 0.12351, 0.14071), tolerance = 1e-3)
m2 <- glm(
neg_c_7d ~ c12hour + e42dep + c161sex + c172code,
data = d,
family = binomial(link = "logit")
)
expect_s3_class(ggpredict(m2, "c12hour", condition = c(c172code = 1), verbose = FALSE), "data.frame")
expect_s3_class(ggpredict(m2, c("c12hour", "c161sex"), condition = c(c172code = 2), verbose = FALSE), "data.frame")
})
)
withr::with_environment(
new.env(),
test_that("ggpredict, condition-lmer", {
skip_if_not_installed("lme4")
data(efc, package = "ggeffects")
efc$grp <- datawizard::to_factor(efc$e15relat)
efc$e42dep <- datawizard::to_factor(efc$e42dep)
d2 <- efc
m3 <- lme4::lmer(
neg_c_7 ~ c12hour + e42dep + c161sex + c172code + (1 | grp),
data = d2
)
pr <- ggpredict(m3, "c12hour", interval = "prediction")
expect_equal(pr$predicted[1], 8.962075, tolerance = 1e-3)
expect_equal(pr$std.error[1], 3.601748, tolerance = 1e-3)
pr <- ggpredict(m3, "c12hour", interval = "prediction", condition = c(c172code = 1))
expect_equal(pr$predicted[1], 8.62045, tolerance = 1e-3)
expect_equal(pr$std.error[1], 3.606084, tolerance = 1e-3)
pr <- ggpredict(m3, "c12hour", interval = "prediction", condition = c(e42dep = "severely dependent"))
expect_equal(pr$predicted[1], 12.83257, tolerance = 1e-3)
expect_equal(pr$std.error[1], 3.601748, tolerance = 1e-3)
pr <- ggpredict(m3, "c12hour", interval = "prediction", condition = c(e42dep = "severely dependent", c172code = 3))
expect_equal(pr$predicted[1], 13.19621, tolerance = 1e-3)
expect_equal(pr$std.error[1], 3.608459, tolerance = 1e-3)
pr <- ggpredict(m3, "c12hour", interval = "prediction", condition = c(e42dep = "severely dependent", c172code = 3, grp = "sibling")) # nolint
expect_equal(pr$predicted[1], 13.19621, tolerance = 1e-3)
expect_equal(pr$std.error[1], 3.608459, tolerance = 1e-3)
pr <- ggpredict(m3, "c12hour", interval = "prediction", condition = c(c172code = 3, grp = "sibling"))
expect_equal(pr$predicted[1], 9.325714, tolerance = 1e-3)
expect_equal(pr$std.error[1], 3.608459, tolerance = 1e-3)
pr <- ggpredict(m3, "c12hour", interval = "prediction", condition = c(grp = "sibling"))
expect_equal(pr$predicted[1], 8.962075, tolerance = 1e-3)
expect_equal(pr$std.error[1], 3.601748, tolerance = 1e-3)
})
)
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