test_that("nonlinear model summary works", {
  
  skip_if_not_installed("nlme")
  
  set.seed(123)
  
  dat <- data.frame(
    id = factor(rep(1:5, each = 4)),
    x = rep(0:3, 5)
  )
  
  dat$y <- 10 * (1 - exp(-0.5 * dat$x)) +
    rnorm(20, 0, 0.2)
  
  m <- fit_nlmm(
    model = y ~ SSasymp(x, Asym, R0, lrc),
    data = dat,
    fixed = Asym + R0 + lrc ~ 1,
    random = Asym ~ 1 | id,
    start = c(
      Asym = 10,
      R0 = 0,
      lrc = log(0.5)
    ),
    control = nlme::nlmeControl(
      maxIter = 100,
      msMaxIter = 200
    )
  )
  
  s <- model_summary(m)
  
  expect_type(s, "list")
  expect_equal(s$model_type, "Nonlinear mixed-effects model")
  expect_true(is.numeric(s$n))
  expect_true(is.finite(s$AIC))
  expect_true(is.finite(s$BIC))
  expect_true(is.numeric(s$logLik))
  expect_true(is.numeric(s$fixed_effects))
  expect_true(is.data.frame(s$random_effects))
})