Nothing
test_that("check_heterogeneity_bias", {
skip_if_not_installed("datawizard")
data(iris)
set.seed(123)
iris$ID <- sample.int(4, nrow(iris), replace = TRUE) # fake-ID
out <- check_heterogeneity_bias(iris, select = c("Sepal.Length", "Petal.Length"), by = "ID")
expect_equal(out, c("Sepal.Length", "Petal.Length"), ignore_attr = TRUE)
expect_output(print(out), "Possible heterogeneity bias due to following predictors: Sepal\\.Length, Petal\\.Length")
out <- check_heterogeneity_bias(iris, select = ~ Sepal.Length + Petal.Length, by = ~ID)
expect_equal(out, c("Sepal.Length", "Petal.Length"), ignore_attr = TRUE)
expect_output(print(out), "Possible heterogeneity bias due to following predictors: Sepal\\.Length, Petal\\.Length")
m <- lm(Sepal.Length ~ Petal.Length + Petal.Width + Species + ID, data = iris)
expect_error(
check_heterogeneity_bias(m, select = c("Sepal.Length", "Petal.Length"), by = "ID"),
regex = "no mixed model"
)
skip_if_not_installed("lme4")
m <- lme4::lmer(Sepal.Length ~ Petal.Length + Petal.Width + Species + (1 | ID), data = iris)
out <- check_heterogeneity_bias(m, select = c("Sepal.Length", "Petal.Length"), by = "ID")
expect_equal(out, c("Petal.Length", "Petal.Width", "Species"), ignore_attr = TRUE)
expect_output(
print(out),
"Possible heterogeneity bias due to following predictors: Petal\\.Length, Petal\\.Width, Species"
)
out <- check_heterogeneity_bias(m, select = ~ Sepal.Length + Petal.Length, by = ~ID)
expect_equal(out, c("Petal.Length", "Petal.Width", "Species"), ignore_attr = TRUE)
expect_output(
print(out),
"Possible heterogeneity bias due to following predictors: Petal\\.Length, Petal\\.Width, Species"
)
})
test_that("check_heterogeneity_bias", {
skip_if_not_installed("datawizard", minimum_version = "0.12.3")
data(efc, package = "datawizard")
dat <- na.omit(efc)
dat$e42dep <- factor(dat$e42dep)
dat$c172code <- factor(dat$c172code)
out <- check_heterogeneity_bias(
dat,
select = "c12hour",
by = c("e42dep", "c172code"),
nested = TRUE
)
expect_equal(out, "c12hour", ignore_attr = TRUE)
})
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