tests/testthat/test-estimate_grouplevel.R

In easystats/estimate: Estimation of Model-Based Predictions, Contrasts and Means

test_that("estimate_grouplevel - lme4", {
  skip_if_not_installed("lme4")
  set.seed(333)
  data <- lme4::sleepstudy

  # Random intercept
  model <- lme4::lmer(Reaction ~ Days + (1 | Subject), data = data)
  random <- estimate_grouplevel(model)
  expect_equal(nrow(random), length(unique(data$Subject)))
  expect_equal(nrow(reshape_grouplevel(random)), nrow(data))

  # 2 random intercepts
  model <- lme4::lmer(mpg ~ wt + (1 | gear) + (1 | carb), data = mtcars)
  random <- estimate_grouplevel(model)
  expect_equal(nrow(random), length(c(unique(mtcars$gear), unique(mtcars$carb))))
  expect_equal(nrow(reshape_grouplevel(random)), nrow(mtcars))

  # Random slope and intercept
  model <- lme4::lmer(Reaction ~ Days + (1 + Days | Subject), data = data)
  random <- estimate_grouplevel(model)
  expect_equal(nrow(random), 2 * length(unique(data$Subject)))
  expect_equal(nrow(reshape_grouplevel(random)), nrow(data))

  # Nested random factors
  set.seed(33)
  data$grp <- sample(letters[1:5], size = 180, replace = TRUE)
  data$subgrp <- NA
  for (i in letters[1:5]) {
    filter_group <- data$grp == i
    data$subgrp[filter_group] <- sample(LETTERS, size = sum(filter_group), replace = TRUE)
  }
  model <- lme4::lmer(Reaction ~ Days + (1 | grp / subgrp) + (1 | Subject), data = data)
  random <- estimate_grouplevel(model)
  expect_equal(nrow(random), sum(sapply(coef(model), nrow)))

  reshaped <- reshape_grouplevel(random)
  expect_equal(nrow(reshaped), nrow(data))
  ref <- insight::get_data(model)[insight::find_random(model, split_nested = TRUE, flatten = TRUE)]
  all(reshaped$Subject == ref$Subject)
  all(reshaped$grp == ref$grp)
  all(reshaped$subgrp == ref$subgrp)
})