diff --git a/tests/testthat/test-model_parameters_robust.R b/tests/testthat/test-model_parameters_robust.R
index 2d4564cf5..c5a18e5bb 100644
--- a/tests/testthat/test-model_parameters_robust.R
+++ b/tests/testthat/test-model_parameters_robust.R
@@ -8,41 +8,31 @@ model <- lm(mpg ~ wt * am + cyl + gear, data = mtcars)
 test_that("model_parameters, robust CL", {
   params1 <- model_parameters(
     model,
-    robust = TRUE,
-    vcov_estimation = "CL",
-    vcov_type = "HC1",
-    verbose = FALSE
-  )
-  params2 <- model_parameters(
-    model,
-    robust = TRUE,
-    vcov_estimation = "CL",
+    vcov = "CL",
     vcov_args = list(type = "HC1"),
     verbose = FALSE
   )
   robust_se <- unname(sqrt(diag(sandwich::vcovCL(model))))
   expect_equal(params1$SE, robust_se, tolerance = 1e-3)
   expect_equal(params1$p, c(0, 0.00695, 0.00322, 0.00435, 0.94471, 0.00176), tolerance = 1e-3)
-  expect_equal(params2$SE, robust_se, tolerance = 1e-3)
-  expect_equal(params2$p, c(0, 0.00695, 0.00322, 0.00435, 0.94471, 0.00176), tolerance = 1e-3)
 })
 
 test_that("model_parameters, robust", {
-  params <- model_parameters(model, robust = TRUE, verbose = FALSE)
+  params <- model_parameters(model, vcov = "HC", verbose = FALSE)
   robust_se <- unname(sqrt(diag(sandwich::vcovHC(model))))
   expect_equal(params$SE, robust_se, tolerance = 1e-3)
   expect_equal(params$p, c(0, 0.0259, 0.01478, 0.01197, 0.95238, 0.01165), tolerance = 1e-3)
 })
 
 test_that("ci, robust", {
-  params <- ci(model, robust = TRUE, verbose = FALSE)
+  params <- ci(model, vcov = "HC", verbose = FALSE)
   robust_se <- unname(sqrt(diag(sandwich::vcovHC(model))))
   upper_ci <- as.vector(coef(model) + qt(0.975, df.residual(model)) * robust_se)
   expect_equal(params$CI_high, upper_ci, tolerance = 1e-3, ignore_attr = TRUE)
 })
 
 test_that("model_parameters, robust CL", {
-  params <- model_parameters(model, robust = TRUE, vcov_estimation = "CL", vcov_type = "HC1", verbose = FALSE)
+  params <- model_parameters(model, vcov = "vcovCL", verbose = FALSE)
   robust_se <- unname(sqrt(diag(sandwich::vcovCL(model))))
   expect_equal(params$SE, robust_se, tolerance = 1e-3)
   expect_equal(params$p, c(0, 0.00695, 0.00322, 0.00435, 0.94471, 0.00176), tolerance = 1e-3)
@@ -51,7 +41,7 @@ test_that("model_parameters, robust CL", {
 model2 <- lm(mpg ~ wt * am + cyl + gear, data = datawizard::standardize(mtcars))
 
 test_that("model_parameters, robust", {
-  params <- model_parameters(model, standardize = "refit", robust = TRUE, verbose = FALSE)
+  params <- model_parameters(model, standardize = "refit", vcov = "HC", verbose = FALSE)
   robust_se <- unname(sqrt(diag(sandwich::vcovHC(model2))))
   expect_equal(params$SE, robust_se, tolerance = 1e-3)
   expect_equal(params$p, c(0.28624, 0.0259, 0.43611, 0.01197, 0.95238, 0.01165), tolerance = 1e-3)
@@ -67,8 +57,7 @@ test_that("model_parameters, robust CR", {
   params <- model_parameters(
     model,
     robust = TRUE,
-    vcov_estimation = "CR",
-    vcov_type = "CR1",
+    vcov = "CR1",
     vcov_args = list(cluster = iris$cluster),
     verbose = FALSE
   )
@@ -86,57 +75,55 @@ data(mtcars)
 mtcars$am <- as.factor(mtcars$am)
 model <- lm(mpg ~ wt * am + cyl + gear, data = mtcars)
 
-if (packageVersion("parameters") >= "0.17.0") {
-  test_that("model_parameters, robust", {
-    expect_warning(expect_warning(expect_warning(model_parameters(model, robust = TRUE))))
-    params <- model_parameters(model, vcov = "HC3")
-    robust_se <- unname(sqrt(diag(sandwich::vcovHC(model))))
-    expect_equal(params$SE, robust_se, tolerance = 1e-3)
-    expect_equal(params$p, c(0, 0.0259, 0.01478, 0.01197, 0.95238, 0.01165), tolerance = 1e-3)
-  })
-
-  test_that("ci, robust", {
-    params <- ci(model, vcov = "HC3")
-    robust_se <- unname(sqrt(diag(sandwich::vcovHC(model))))
-    upper_ci <- as.vector(coef(model) + qt(0.975, df.residual(model)) * robust_se)
-    expect_equal(params$CI_high, upper_ci, tolerance = 1e-3, ignore_attr = TRUE)
-  })
-
-  test_that("model_parameters, robust CL", {
-    params <- model_parameters(model, vcov = "vcovCL", vcov_args = list(type = "HC1"))
-    robust_se <- unname(sqrt(diag(sandwich::vcovCL(model))))
-    expect_equal(params$SE, robust_se, tolerance = 1e-3)
-    expect_equal(params$p, c(0, 0.00695, 0.00322, 0.00435, 0.94471, 0.00176), tolerance = 1e-3)
-  })
-
-  d <- datawizard::standardize(mtcars)
-  model2 <- lm(mpg ~ wt * am + cyl + gear, data = d)
-
-  test_that("model_parameters, robust", {
-    params <- model_parameters(model, standardize = "refit", vcov = "HC3")
-    robust_se <- unname(sqrt(diag(sandwich::vcovHC(model2))))
-    expect_equal(params$SE, robust_se, tolerance = 1e-3)
-    expect_equal(params$p, c(0.28624, 0.0259, 0.43611, 0.01197, 0.95238, 0.01165), tolerance = 1e-3)
-  })
-
-
-  # cluster-robust standard errors, using clubSandwich
-  data(iris)
-  model <- lm(Petal.Length ~ Sepal.Length * Species, data = iris)
-  iris$cluster <- factor(rep(LETTERS[1:8], length.out = nrow(iris)))
-
-  test_that("model_parameters, robust CR", {
-    params <- model_parameters(model, vcov = "vcovCR", vcov_args = list(type = "CR1", cluster = iris$cluster))
-    robust_se <- unname(sqrt(diag(clubSandwich::vcovCR(model, type = "CR1", cluster = iris$cluster))))
-    expect_equal(params$SE, robust_se, tolerance = 1e-3)
-    expect_equal(params$p, c(0.01246, 0.04172, 0.18895, 0.57496, 0, 0), tolerance = 1e-3)
-  })
-
-  test_that("model_parameters, normal", {
-    params <- model_parameters(model)
-    expect_equal(params$p, c(0.13267, 0.21557, 0.36757, 0.77012, 3e-05, 0), tolerance = 1e-3)
-  })
-}
+test_that("model_parameters, robust", {
+  expect_warning(expect_warning(expect_warning(model_parameters(model, robust = TRUE))))
+  params <- model_parameters(model, vcov = "HC3")
+  robust_se <- unname(sqrt(diag(sandwich::vcovHC(model))))
+  expect_equal(params$SE, robust_se, tolerance = 1e-3)
+  expect_equal(params$p, c(0, 0.0259, 0.01478, 0.01197, 0.95238, 0.01165), tolerance = 1e-3)
+})
+
+test_that("ci, robust", {
+  params <- ci(model, vcov = "HC3")
+  robust_se <- unname(sqrt(diag(sandwich::vcovHC(model))))
+  upper_ci <- as.vector(coef(model) + qt(0.975, df.residual(model)) * robust_se)
+  expect_equal(params$CI_high, upper_ci, tolerance = 1e-3, ignore_attr = TRUE)
+})
+
+test_that("model_parameters, robust CL", {
+  params <- model_parameters(model, vcov = "vcovCL", vcov_args = list(type = "HC1"))
+  robust_se <- unname(sqrt(diag(sandwich::vcovCL(model))))
+  expect_equal(params$SE, robust_se, tolerance = 1e-3)
+  expect_equal(params$p, c(0, 0.00695, 0.00322, 0.00435, 0.94471, 0.00176), tolerance = 1e-3)
+})
+
+d <- datawizard::standardize(mtcars)
+model2 <- lm(mpg ~ wt * am + cyl + gear, data = d)
+
+test_that("model_parameters, robust", {
+  params <- model_parameters(model, standardize = "refit", vcov = "HC3")
+  robust_se <- unname(sqrt(diag(sandwich::vcovHC(model2))))
+  expect_equal(params$SE, robust_se, tolerance = 1e-3)
+  expect_equal(params$p, c(0.28624, 0.0259, 0.43611, 0.01197, 0.95238, 0.01165), tolerance = 1e-3)
+})
+
+
+# cluster-robust standard errors, using clubSandwich
+data(iris)
+model <- lm(Petal.Length ~ Sepal.Length * Species, data = iris)
+iris$cluster <- factor(rep(LETTERS[1:8], length.out = nrow(iris)))
+
+test_that("model_parameters, robust CR", {
+  params <- model_parameters(model, vcov = "vcovCR", vcov_args = list(type = "CR1", cluster = iris$cluster))
+  robust_se <- unname(sqrt(diag(clubSandwich::vcovCR(model, type = "CR1", cluster = iris$cluster))))
+  expect_equal(params$SE, robust_se, tolerance = 1e-3)
+  expect_equal(params$p, c(0.01246, 0.04172, 0.18895, 0.57496, 0, 0), tolerance = 1e-3)
+})
+
+test_that("model_parameters, normal", {
+  params <- model_parameters(model)
+  expect_equal(params$p, c(0.13267, 0.21557, 0.36757, 0.77012, 3e-05, 0), tolerance = 1e-3)
+})
 
 test_that("ci_ml1, robust", {
   skip("TODO: this one actually is not correct.")