Nothing

```
context("Test ratio_test")
# test if ratio_test works properly for probit -----
test_that("Determine if ratio_test runs properly for probits", {
s <- glm((response / total) ~ log10(dose),
data = lamprey_tox[lamprey_tox$nominal_dose != 0, ],
subset = c(month == "September"),
weights = total,
family = binomial(link = "probit"))
j <- glm((response / total) ~ log10(dose),
data = lamprey_tox[lamprey_tox$nominal_dose != 0, ],
subset = c(month == "June"),
weights = total,
family = binomial(link = "probit"))
ratios <- ratio_test(model_1 = j, model_2 = s, percentage = 50)
ratios
expect_equal(ratios$dose_1, expected = 2.66, tolerance = 0.001)
expect_equal(ratios$dose_2, expected = 2.12, tolerance = 0.001)
expect_equal(ratios$se, expected = 0.0387, tolerance = 0.001)
expect_equal(ratios$test_stat, expected = 2.544, tolerance = 0.001)
expect_equal(ratios$p_value, expected = 0.0109, tolerance = 0.0001)
})
# test if ratio_test works for logits ------
test_that("Determine if ratio_test runs properly for logits", {
s <- glm((response / total) ~ log10(dose),
data = lamprey_tox[lamprey_tox$nominal_dose != 0, ],
subset = c(month == "September"),
weights = total,
family = binomial(link = "logit"))
j <- glm((response / total) ~ log10(dose),
data = lamprey_tox[lamprey_tox$nominal_dose != 0, ],
subset = c(month == "June"),
weights = total,
family = binomial(link = "logit"))
ratios <- ratio_test(model_1 = j, model_2 = s, percentage = 50,
type = "logit")
ratios
expect_equal(ratios$dose_1, expected = 2.654, tolerance = 0.001)
expect_equal(ratios$dose_2, expected = 2.12, tolerance = 0.001)
expect_equal(ratios$se, expected = 0.0374, tolerance = 0.001)
expect_equal(ratios$test_stat, expected = 2.621, tolerance = 0.001)
expect_equal(ratios$p_value, expected = 0.0087, tolerance = 0.0001)
})
# test if ratio_test returns proper values when does isn't log transformed ----
test_that("Determine if ratio_test runs properly
if dose isn't log transformed", {
s <- glm((response / total) ~ dose,
data = lamprey_tox[lamprey_tox$nominal_dose != 0, ],
subset = c(month == "September"),
weights = total,
family = binomial(link = "probit"))
j <- glm((response / total) ~ dose,
data = lamprey_tox[lamprey_tox$nominal_dose != 0, ],
subset = c(month == "June"),
weights = total,
family = binomial(link = "probit"))
ratios <- ratio_test(model_1 = j, model_2 = s,
percentage = 50, log_x = FALSE)
ratios
expect_equal(ratios$dose_1, expected = 2.666, tolerance = 0.001)
expect_equal(ratios$dose_2, expected = 2.140, tolerance = 0.001)
expect_equal(ratios$se, expected = 0.0292, tolerance = 0.001)
expect_equal(ratios$test_stat, expected = 7.508, tolerance = 0.001)
expect_equal(ratios$p_value, expected = 5.962518e-14, tolerance = 0.0001)
})
# test errors -----
test_that("Test errors if model 2 isn't supplied", {
s <- glm((response / total) ~ log10(dose),
data = lamprey_tox[lamprey_tox$nominal_dose != 0, ],
subset = c(month == "September"),
weights = total,
family = binomial(link = "probit"))
j <- glm((response / total) ~ log10(dose),
data = lamprey_tox[lamprey_tox$nominal_dose != 0, ],
subset = c(month == "June"),
weights = total,
family = binomial(link = "probit"))
expect_error(ratio_test(model_1 = j, percentage = 50))
})
test_that("Test errors if model 1 isn't supplied", {
s <- glm((response / total) ~ log10(dose),
data = lamprey_tox[lamprey_tox$nominal_dose != 0, ],
subset = c(month == "September"),
weights = total,
family = binomial(link = "probit"))
j <- glm((response / total) ~ log10(dose),
data = lamprey_tox[lamprey_tox$nominal_dose != 0, ],
subset = c(month == "June"),
weights = total,
family = binomial(link = "probit"))
expect_error(ratio_test(model_2 = s, percentage = 50))
})
# test warning messages -----
test_that("Test warning for when percentage isn't supplied", {
s <- glm((response / total) ~ log10(dose),
data = lamprey_tox[lamprey_tox$nominal_dose != 0, ],
subset = c(month == "September"),
weights = total,
family = binomial(link = "probit"))
j <- glm((response / total) ~ log10(dose),
data = lamprey_tox[lamprey_tox$nominal_dose != 0, ],
subset = c(month == "June"),
weights = total,
family = binomial(link = "probit"))
expect_warning(ratio_test(model_1 = j, model_2 = s))
})
```

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