diff --git a/tests/testthat/test-model_parameters.anova.R b/tests/testthat/test-model_parameters.anova.R
index a05a82c8d..acc5719d3 100644
--- a/tests/testthat/test-model_parameters.anova.R
+++ b/tests/testthat/test-model_parameters.anova.R
@@ -8,7 +8,7 @@ test_that("model_parameters.anova", {
   a <- anova(m, test = "Chisq")
   mp <- model_parameters(a)
 
-  expect_equal(colnames(mp), c("Parameter", "df", "Deviance", "df_error", "Deviance_error", "p"))
+  expect_named(mp, c("Parameter", "df", "Deviance", "df_error", "Deviance_error", "p"))
   expect_equal(mp$Deviance_error, c(43.22973, 29.67517, 19.23255, 10.48692), tolerance = 1e-3)
   expect_equal(mp$p, c(NA, 0.00023, 0.00123, 0.01262), tolerance = 1e-3)
   expect_snapshot(mp)
@@ -18,7 +18,7 @@ test_that("model_parameters.anova", {
   skip_if_not_installed("car")
   a <- car::Anova(m, type = 3, test.statistic = "F")
   mp <- model_parameters(a)
-  expect_equal(colnames(mp), c("Parameter", "Sum_Squares", "df", "Mean_Square", "F", "p"))
+  expect_named(mp, c("Parameter", "Sum_Squares", "df", "Mean_Square", "F", "p"))
   expect_equal(mp[["F"]], c(53.40138, 60.42944, 13.96887, NA), tolerance = 1e-3)
 })
 
@@ -38,13 +38,13 @@ test_that("linear hypothesis tests", {
   expect_equal(p1, p2, ignore_attr = TRUE)
   expect_equal(p1, p3, ignore_attr = TRUE)
   expect_equal(p1, p4, ignore_attr = TRUE)
-  expect_equal(nrow(p1), 2)
-  expect_equal(p1$Parameter, c("(Intercept) = 0", "repwt = 1"))
+  expect_identical(nrow(p1), 2L)
+  expect_identical(p1$Parameter, c("(Intercept) = 0", "repwt = 1"))
 
   mod.duncan <- lm(prestige ~ income + education, data = Duncan)
   p <- parameters(car::linearHypothesis(mod.duncan, "1*income - 1*education + 1 = 1"))
-  expect_equal(nrow(p), 1)
-  expect_equal(p$Parameter, "income - education = 0")
+  expect_identical(nrow(p), 1L)
+  expect_identical(p$Parameter, "income - education = 0")
 })
 
 test_that("print-model_parameters", {
@@ -62,7 +62,7 @@ test_that("model_parameters_Anova.mlm", {
   a <- car::Anova(m, type = 3, test.statistic = "Pillai")
   mp <- model_parameters(a, verbose = FALSE)
 
-  expect_equal(colnames(mp), c("Parameter", "df", "Statistic", "df_num", "df_error", "F", "p"))
+  expect_named(mp, c("Parameter", "df", "Statistic", "df_num", "df_error", "F", "p"))
   expect_equal(mp[["F"]], c(158.2578, 6.60593, 3.71327, 3.28975), tolerance = 1e-3)
   expect_equal(mp$Statistic, c(0.9268, 0.67387, 0.22903, 0.4039), tolerance = 1e-3)
 })
@@ -75,7 +75,7 @@ test_that("model_parameters_Anova.mlm", {
   m <- MASS::polr(Sat ~ Infl + Type + Cont, weights = Freq, data = housing)
   a <- car::Anova(m)
   mp <- model_parameters(a)
-  expect_equal(colnames(mp), c("Parameter", "Chi2", "df", "p"))
+  expect_named(mp, c("Parameter", "Chi2", "df", "p"))
   expect_equal(mp$Chi2, c(108.2392, 55.91008, 14.30621), tolerance = 1e-3)
 })
 
@@ -118,16 +118,16 @@ test_that("anova type | lm", {
   m <- lm(mpg ~ factor(cyl) * hp + disp, mtcars)
 
   a1 <- aov(m)
-  expect_equal(attr(model_parameters(a1), "anova_type"), 1)
+  expect_identical(attr(model_parameters(a1), "anova_type"), 1L)
 
   a1 <- anova(m)
-  expect_equal(attr(model_parameters(a1), "anova_type"), 1)
+  expect_identical(attr(model_parameters(a1), "anova_type"), 1L)
 
   a2 <- car::Anova(m, type = 2)
   a3 <- car::Anova(m, type = 3)
-  expect_equal(attr(model_parameters(a2), "anova_type"), 2)
+  expect_identical(attr(model_parameters(a2), "anova_type"), 2L)
   expect_message(
-    expect_equal(attr(model_parameters(a3), "anova_type"), 3),
+    expect_identical(attr(model_parameters(a3), "anova_type"), 3L),
     "Type 3 ANOVAs only give"
   )
 
@@ -151,15 +151,15 @@ test_that("anova type | mlm", {
   m <- lm(cbind(mpg, drat) ~ factor(cyl) * hp + disp, mtcars)
 
   a1 <- aov(m)
-  expect_equal(attr(model_parameters(a1), "anova_type"), 1)
+  expect_identical(attr(model_parameters(a1), "anova_type"), 1L)
 
   a1 <- anova(m)
-  expect_equal(attr(model_parameters(a1), "anova_type"), 1)
+  expect_identical(attr(model_parameters(a1), "anova_type"), 1L)
 
   a2 <- car::Anova(m, type = 2)
   a3 <- car::Anova(m, type = 3)
-  expect_equal(attr(model_parameters(a2), "anova_type"), 2)
-  expect_equal(attr(model_parameters(a3, verbose = FALSE), "anova_type"), 3)
+  expect_identical(attr(model_parameters(a2), "anova_type"), 2L)
+  expect_identical(attr(model_parameters(a3, verbose = FALSE), "anova_type"), 3L)
 })
 
 test_that("anova type | glm", {
@@ -168,13 +168,13 @@ test_that("anova type | glm", {
   m <- suppressWarnings(glm(am ~ factor(cyl) * hp + disp, mtcars, family = binomial()))
 
   a1 <- anova(m)
-  expect_equal(attr(model_parameters(a1), "anova_type"), 1)
+  expect_identical(attr(model_parameters(a1), "anova_type"), 1L)
 
   a2 <- suppressWarnings(car::Anova(m, type = 2))
   a3 <- suppressWarnings(car::Anova(m, type = 3))
-  expect_equal(attr(model_parameters(a2), "anova_type"), 2)
+  expect_identical(attr(model_parameters(a2), "anova_type"), 2L)
   expect_message(
-    expect_equal(attr(model_parameters(a3), "anova_type"), 3),
+    expect_identical(attr(model_parameters(a3), "anova_type"), 3L),
     "Type 3 ANOVAs only give"
   )
 })
@@ -185,37 +185,37 @@ test_that("anova type | lme4", {
   skip_if_not_installed("car")
 
   m1 <- lme4::lmer(mpg ~ factor(cyl) * hp + disp + (1 | gear), mtcars)
-  suppressMessages(
+  suppressMessages({
     m2 <- lme4::glmer(carb ~ factor(cyl) * hp + disp + (1 | gear), mtcars,
       family = poisson()
     )
-  )
+  })
 
   a1 <- anova(m1)
-  expect_equal(attr(model_parameters(a1), "anova_type"), 1)
+  expect_identical(attr(model_parameters(a1), "anova_type"), 1L)
 
   a1 <- anova(m2)
-  expect_equal(attr(model_parameters(a1), "anova_type"), 1)
+  expect_identical(attr(model_parameters(a1), "anova_type"), 1L)
 
   a3 <- anova(lmerTest::as_lmerModLmerTest(m1))
   expect_message(
-    expect_equal(attr(model_parameters(a3), "anova_type"), 3),
+    expect_identical(attr(model_parameters(a3), "anova_type"), 3L),
     "Type 3 ANOVAs only give"
   )
 
   a2 <- car::Anova(m1, type = 2)
   a3 <- car::Anova(m1, type = 3)
-  expect_equal(attr(model_parameters(a2), "anova_type"), 2)
+  expect_identical(attr(model_parameters(a2), "anova_type"), 2L)
   expect_message(
-    expect_equal(attr(model_parameters(a3), "anova_type"), 3),
+    expect_identical(attr(model_parameters(a3), "anova_type"), 3L),
     "Type 3 ANOVAs only give"
   )
 
   a2 <- car::Anova(m2, type = 2)
   a3 <- car::Anova(m2, type = 3)
-  expect_equal(attr(model_parameters(a2), "anova_type"), 2)
+  expect_identical(attr(model_parameters(a2), "anova_type"), 2L)
   expect_message(
-    expect_equal(attr(model_parameters(a3), "anova_type"), 3),
+    expect_identical(attr(model_parameters(a3), "anova_type"), 3L),
     "Type 3 ANOVAs only give"
   )
 })
@@ -225,15 +225,15 @@ test_that("anova type | afex + Anova.mlm", {
 
   data(obk.long, package = "afex")
 
-  suppressMessages(
+  suppressMessages({
     m <- afex::aov_ez("id", "value", obk.long,
       between = c("treatment", "gender"),
       within = c("phase", "hour"), observed = "gender"
     )
-  )
+  })
 
-  expect_equal(attr(model_parameters(m), "anova_type"), 3)
-  expect_equal(attr(model_parameters(m$Anova, verbose = FALSE), "anova_type"), 3)
+  expect_identical(attr(model_parameters(m), "anova_type"), 3L)
+  expect_identical(attr(model_parameters(m$Anova, verbose = FALSE), "anova_type"), 3L)
 })
 
 test_that("anova rms", {
@@ -242,20 +242,21 @@ test_that("anova rms", {
   a <- anova(m)
   mp <- model_parameters(a)
 
-  expect_equal(attr(mp, "anova_type"), 2)
-  expect_equal(mp$Parameter, c("cyl", "disp", "hp", "drat", "Total", "Residuals"))
-  expect_equal(colnames(mp), c("Parameter", "Sum_Squares_Partial", "df", "Mean_Square", "F", "p"))
+  expect_identical(attr(mp, "anova_type"), 2L)
+  expect_identical(mp$Parameter, c("cyl", "disp", "hp", "drat", "Total", "Residuals"))
+  expect_identical(colnames(mp), c("Parameter", "Sum_Squares_Partial", "df", "Mean_Square", "F", "p"))
   expect_equal(mp$Sum_Squares_Partial, data.frame(a)$Partial.SS, tolerance = 1e-3)
 })
 
 test_that("anova rms", {
   skip_if_not_installed("rms")
+  skip_if(getRversion() < "4.2.0")
   m <- rms::orm(mpg ~ cyl + disp + hp + drat, data = mtcars)
   a <- anova(m)
   mp <- model_parameters(a)
 
-  expect_equal(attr(mp, "anova_type"), 2)
-  expect_equal(mp$Parameter, c("cyl", "disp", "hp", "drat", "Total"))
-  expect_equal(colnames(mp), c("Parameter", "Chi2", "df", "p"))
+  expect_identical(attr(mp, "anova_type"), 2L)
+  expect_identical(mp$Parameter, c("cyl", "disp", "hp", "drat", "Total"))
+  expect_named(mp, c("Parameter", "Chi2", "df", "p"))
   expect_equal(mp$Chi2, data.frame(a)$Chi.Square, tolerance = 1e-3)
 })