Nothing
test_that("check_collinearity works correctly for multivariable models", {
library(gtregression)
library(dplyr)
library(mlbench)
data(PimaIndiansDiabetes2, package = "mlbench")
pima <- PimaIndiansDiabetes2 |>
filter(!is.na(diabetes)) |>
mutate(diabetes = ifelse(diabetes == "pos", 1, 0))
# multivariable linear model
multi_lm <- multi_reg(
data = pima,
outcome = "glucose",
exposures = c("age", "mass", "pressure"),
approach = "linear"
)
vif_tbl <- check_collinearity(multi_lm)
expect_s3_class(vif_tbl, "tbl_df")
expect_true(all(c("Variable", "VIF", "Interpretation") %in% names(vif_tbl)))
expect_equal(nrow(vif_tbl), 3)
})
test_that("check_collinearity throws error for univariate models", {
data(PimaIndiansDiabetes2, package = "mlbench")
pima <- PimaIndiansDiabetes2 |>
filter(!is.na(diabetes)) |>
mutate(diabetes = ifelse(diabetes == "pos", 1, 0))
uni_lm <- uni_reg(
data = pima,
outcome = "glucose",
exposures = c("age", "mass", "pressure"),
approach = "linear"
)
expect_error(
check_collinearity(uni_lm),
"VIF is not applicable for univariate models"
)
})
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