Nothing
test_that("A level is missing from the reference sample should raise a warning", {
ref_sample <-
data.frame(
pid = c(1, 2, 3, 4, 5),
hid = c(1, 1, 2, 2, 3),
gender = c("male", "female", "male", "male", "female"),
marital_status = c("married", "single", "married", "married", "married"),
hhsize = c(2, 2, 2, 2, 1)
)
p_control <-
data.frame(
gender = rep(c("male", "female"), 2),
marital_status = c(rep("married", 2), rep("single", 2)),
count = 1:4
)
h_control <-
data.frame(
hhsize = c(1, 2),
count = c(2, 1)
)
toy_problem <-
ml_problem(
ref_sample = ref_sample,
controls = list(
individual = list(p_control),
group = list(h_control)
),
field_names = special_field_names("hid", "pid", count = "count")
)
expect_warning(
ml_fit(toy_problem, algorithm = "ipu"),
regexp = "Found missing observations for the following non-zero controls: gender_i_male:marital_status_i_single"
)
})
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