Nothing
test_that("interaction_models returns a list with expected names", {
library(gtregression)
library(dplyr)
data("PimaIndiansDiabetes2", package = "mlbench")
pima_data <- PimaIndiansDiabetes2 |>
mutate(diabetes = ifelse(diabetes == "pos", 1, 0)) |>
mutate(
bmi = factor(
case_when(
mass < 25 ~ "Normal",
mass >= 25 & mass < 30 ~ "Overweight",
mass >= 30 ~ "Obese"
),
levels = c("Normal", "Overweight", "Obese")
),
age_cat = factor(
case_when(
age < 30 ~ "Young",
age >= 30 & age < 50 ~ "Middle-aged",
age >= 50 ~ "Older"
),
levels = c("Young", "Middle-aged", "Older")
),
glucose_cat = factor(
case_when(
glucose < 140 ~ "Normal",
glucose >= 140 ~ "High"
),
levels = c("Normal", "High")
)
)
result <- interaction_models(
data = pima_data,
outcome = "diabetes",
exposure = "age_cat",
effect_modifier = "glucose_cat",
approach = "logit"
)
expect_type(result, "list")
expect_named(result, c("model_no_interaction",
"model_with_interaction", "p_value", "test"))
})
test_that("interaction_models handles robpoisson approach", {
library(gtregression)
library(dplyr)
data("PimaIndiansDiabetes2", package = "mlbench")
pima_data <- PimaIndiansDiabetes2 |>
mutate(diabetes = ifelse(diabetes == "pos", 1, 0)) |>
mutate(
age_cat = factor(case_when(
age < 30 ~ "Young",
age >= 30 & age < 50 ~ "Middle-aged",
age >= 50 ~ "Older"
)),
glucose_cat = factor(case_when(
glucose < 140 ~ "Normal",
glucose >= 140 ~ "High"
))
)
result <- interaction_models(
data = pima_data,
outcome = "diabetes",
exposure = "age_cat",
effect_modifier = "glucose_cat",
approach = "robpoisson"
)
expect_type(result, "list")
expect_named(result, c("model_no_interaction",
"model_with_interaction", "p_value", "test"))
})
test_that("interaction_models errors with invalid approach", {
library(gtregression)
library(dplyr)
data("PimaIndiansDiabetes2", package = "mlbench")
pima_data <- PimaIndiansDiabetes2 |>
mutate(diabetes = ifelse(diabetes == "pos", 1, 0)) |>
mutate(
age_cat = factor(case_when(
age < 30 ~ "Young",
age >= 30 & age < 50 ~ "Middle-aged",
age >= 50 ~ "Older"
)),
glucose_cat = factor(case_when(
glucose < 140 ~ "Normal",
glucose >= 140 ~ "High"
))
)
expect_error(
interaction_models(
data = pima_data,
outcome = "diabetes",
exposure = "age_cat",
effect_modifier = "glucose_cat",
approach = "invalid"
),
"invalid is not a valid approach for interaction_models"
)
})
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