nursery_data$recommend <- as.character(nursery_data$recommend)
nursery_data$recommend[which(nursery_data$recommend == "not_recom")] <- "0"
nursery_data$recommend[which(nursery_data$recommend == "recommend")] <- "1"
nursery_data$recommend[which(nursery_data$recommend == "very_recom")] <- "2"
nursery_data$recommend[which(nursery_data$recommend == "priority")] <- "3"
nursery_data$recommend[which(nursery_data$recommend == "spec_prior")] <- "4"
nursery_data$recommend <- as.numeric(nursery_data$recommend)

# extract relevant columns
df <- nursery_data[, c("recommend", "children")]
# drop rows with missing values
df <- df[complete.cases(df), ]
# formula to fit
formula <- "recommend ~ children"

test_that("acro_lm without initialising ACRO object first", {
  acroEnv$ac <- NULL
  expect_error(acro_lm(formula = formula, data = df), "ACRO has not been initialised. Please first call acro_init()")
})

test_that("acro_lm works", {
  testthat::skip_on_cran()
  acro_init()
  model <- acro_lm(formula = formula, data = df)
  expect_s3_class(model, "statsmodels.iolib.summary.Summary")
})