tests/testthat/test-glmer.R

In ggeffects: Create Tidy Data Frames of Marginal Effects for 'ggplot' from Model Outputs

.runThisTest <- Sys.getenv("RunAllggeffectsTests") == "yes"

if (.runThisTest && suppressWarnings(
  requiet("testthat") &&
  requiet("ggeffects") &&
  requiet("lme4") &&
  requiet("glmmTMB")
)) {

  # lme4::glmer ----

  data(efc_test)
  fit <- lme4::glmer(
    negc7d ~ c12hour + e42dep + c161sex + c172code + (1 | grp),
      data = efc_test,
      family = binomial(link = "logit")
    )

  test_that("ggpredict, lme4::glmer", {
    pr <- ggpredict(fit, "c12hour")
    expect_equal(
      pr$predicted,
      c(0.34217, 0.34406, 0.34596, 0.34787, 0.34978, 0.3517, 0.35362,
        0.35554, 0.35747, 0.35941, 0.36135, 0.36329, 0.36524, 0.36719,
        0.36915, 0.37111, 0.37307, 0.37504, 0.37702, 0.37899, 0.38098,
        0.38296, 0.38495, 0.38694, 0.38894, 0.39094, 0.39295, 0.39496,
        0.39697, 0.39898, 0.401, 0.40302, 0.40505, 0.40708, 0.40911),
      tolerance = 1e-3,
      ignore_attr = TRUE)
    expect_s3_class(ggpredict(fit, "c12hour"), "data.frame")
    expect_s3_class(ggpredict(fit, c("c12hour", "c161sex")), "data.frame")
    expect_s3_class(ggpredict(fit, c("c12hour", "c161sex", "c172code")), "data.frame")
    expect_s3_class(ggpredict(fit, "c12hour", type = "re"), "data.frame")
    expect_s3_class(ggpredict(fit, c("c12hour", "c161sex"), type = "re"), "data.frame")
    expect_s3_class(ggpredict(fit, c("c12hour", "c161sex", "c172code"), type = "re"), "data.frame")
  })

  test_that("ggeffect, lme4::glmer", {
    pr <- ggeffect(fit, "c12hour")
    expect_equal(
      pr$predicted,
      c(0.34217, 0.34406, 0.34596, 0.34787, 0.34978, 0.3517, 0.35362,
        0.35554, 0.35747, 0.35941, 0.36135, 0.36329, 0.36524, 0.36719,
        0.36915, 0.37111, 0.37307, 0.37504, 0.37702, 0.37899, 0.38098,
        0.38296, 0.38495, 0.38694, 0.38894, 0.39094, 0.39295, 0.39496,
        0.39697, 0.39898, 0.401, 0.40302, 0.40505, 0.40708, 0.40911),
      tolerance = 1e-3,
      ignore_attr = TRUE)
    expect_s3_class(ggeffect(fit, "c12hour"), "data.frame")
    expect_s3_class(ggeffect(fit, c("c12hour", "c161sex")), "data.frame")
    expect_s3_class(ggeffect(fit, c("c12hour", "c161sex", "c172code")), "data.frame")
  })

  test_that("ggemmeans, lme4::glmer", {
    pr <- ggemmeans(fit, "c12hour")
    expect_equal(
      pr$predicted,
      c(0.34217, 0.34406, 0.34596, 0.34787, 0.34978, 0.3517, 0.35362,
        0.35554, 0.35747, 0.35941, 0.36135, 0.36329, 0.36524, 0.36719,
        0.36915, 0.37111, 0.37307, 0.37504, 0.37702, 0.37899, 0.38098,
        0.38296, 0.38495, 0.38694, 0.38894, 0.39094, 0.39295, 0.39496,
        0.39697, 0.39898, 0.401, 0.40302, 0.40505, 0.40708, 0.40911),
      tolerance = 1e-3,
      ignore_attr = TRUE)
    expect_s3_class(ggemmeans(fit, "c12hour"), "data.frame")
    expect_s3_class(ggemmeans(fit, c("c12hour", "c161sex")), "data.frame")
    expect_s3_class(ggemmeans(fit, c("c12hour", "c161sex", "c172code")), "data.frame")
  })



  m <- insight::download_model("merMod_5")
  dd <<- insight::get_data(m, source = "frame")

  test_that("ggpredict, lme4::glmer.nb", {
    expect_s3_class(ggpredict(m, "f1"), "data.frame")
    expect_s3_class(ggpredict(m, "f1", type = "re"), "data.frame")
    expect_s3_class(ggpredict(m, c("f1", "f2")), "data.frame")
    expect_s3_class(ggpredict(m, c("f1", "f2"), type = "re"), "data.frame")
    expect_message(ggemmeans(m, "f1"))
    expect_s3_class(ggemmeans(m, c("f1", "f2")), "data.frame")
  })

  test_that("ggpredict, lme4::glmer.nb-simulate", {
    expect_s3_class(ggpredict(m, c("f1", "f2"), type = "sim"), "data.frame")
  })



  data(cbpp)
  cbpp$trials <- cbpp$size - cbpp$incidence

  m1 <- lme4::glmer(cbind(incidence, trials) ~ period + (1 | herd), data = cbpp, family = binomial)
  m2 <- lme4::glmer(cbind(incidence, size - incidence) ~ period + (1 | herd), data = cbpp, family = binomial)

  test_that("ggpredict, lme4::glmer, cbind", {
    expect_s3_class(ggpredict(m1, "period"), "data.frame")
    expect_s3_class(ggpredict(m2, "period"), "data.frame")
    expect_s3_class(ggpredict(m1, "period", type = "re"), "data.frame")
    expect_s3_class(ggpredict(m2, "period", type = "re"), "data.frame")
    expect_s3_class(ggemmeans(m1, "period"), "data.frame")
    expect_s3_class(ggemmeans(m2, "period"), "data.frame")
  })

  test_that("compare, lme4::glmer, cbind", {
    p1 <- ggpredict(m1, "period")
    p2 <- ggemmeans(m1, "period")
    expect_equal(p1$predicted[1], p2$predicted[1], tolerance = 1e-3)
  })
}