diff --git a/R/test_performance.R b/R/test_performance.R
index d30f86035..7c1bbb7d8 100644
--- a/R/test_performance.R
+++ b/R/test_performance.R
@@ -437,7 +437,7 @@ test_performance.ListNonNestedRegressions <- function(objects,
     insight::format_error("At least two models are required to test them.")
   }
 
-  if (same_response && !inherits(objects, "ListLavaan") && !attributes(objects)$same_response) {
+  if (same_response && !inherits(objects, "ListLavaan") && isFALSE(attributes(objects)$same_response)) {
     insight::format_error(
       "The models' dependent variables don't have the same data, which is a prerequisite to compare them. Probably the proportion of missing data differs between models."
     )
diff --git a/R/test_wald.R b/R/test_wald.R
index b7ec3cead..c97b81c76 100644
--- a/R/test_wald.R
+++ b/R/test_wald.R
@@ -69,7 +69,7 @@ test_wald.ListNonNestedRegressions <- function(objects, ...) {
 
   out <- data.frame(
     df = dfs,
-    df_diff = dfs_diff,
+    df_diff = round(dfs_diff),
     stringsAsFactors = FALSE
   )
 
diff --git a/tests/testthat/test-test_likelihoodratio.R b/tests/testthat/test-test_likelihoodratio.R
index 91b6ec8ce..763f64780 100644
--- a/tests/testthat/test-test_likelihoodratio.R
+++ b/tests/testthat/test-test_likelihoodratio.R
@@ -1,113 +1,109 @@
-if (requiet("testthat") &&
-  requiet("performance") &&
-  requiet("lavaan")) {
-  test_that("test_likelihoodratio - regression models", {
-    m1 <- lm(mpg ~ wt + cyl + gear + disp, data = mtcars)
-    m2 <- lm(mpg ~ wt + cyl + gear, data = mtcars)
-    m3 <- lm(mpg ~ wt + cyl, data = mtcars)
-
-    # stats::anova()
-    rez <- test_likelihoodratio(m1, m2, m3, estimator = "OLS")
-    ref <- anova(m1, m2, m3, test = "LRT")
-    expect_equal(ref$`Pr(>Chi)`, rez$p, tolerance = 1e-03)
-
-    rez <- test_likelihoodratio(m3, m2, m1, estimator = "OLS")
-    ref <- anova(m3, m2, m1, test = "LRT")
-    expect_equal(ref$`Pr(>Chi)`, rez$p, tolerance = 1e-03)
-
-    # lmtest::lrtest()
-    rez <- test_likelihoodratio(m1, m2, m3, estimator = "ML")
-    p <- c(NA, 0.5302030, 0.4747344) # lmtest::lrtest(m1, m2, m3)$`Pr(>Chisq)`
-    expect_equal(p, rez$p, tolerance = 1e-03)
-
-    rez <- test_likelihoodratio(m3, m2, m1, estimator = "ML")
-    p <- c(NA, 0.4747344, 0.5302030) # lmtest::lrtest(m3, m2, m1)$`Pr(>Chisq)`
-    expect_equal(p, rez$p, tolerance = 1e-03)
+test_that("test_likelihoodratio - regression models", {
+  m1 <- lm(mpg ~ wt + cyl + gear + disp, data = mtcars)
+  m2 <- lm(mpg ~ wt + cyl + gear, data = mtcars)
+  m3 <- lm(mpg ~ wt + cyl, data = mtcars)
+
+  # stats::anova()
+  rez <- test_likelihoodratio(m1, m2, m3, estimator = "OLS")
+  ref <- anova(m1, m2, m3, test = "LRT")
+  expect_equal(ref$`Pr(>Chi)`, rez$p, tolerance = 1e-03)
+
+  rez <- test_likelihoodratio(m3, m2, m1, estimator = "OLS")
+  ref <- anova(m3, m2, m1, test = "LRT")
+  expect_equal(ref$`Pr(>Chi)`, rez$p, tolerance = 1e-03)
+
+  # lmtest::lrtest()
+  rez <- test_likelihoodratio(m1, m2, m3, estimator = "ML")
+  p <- c(NA, 0.5302030, 0.4747344) # lmtest::lrtest(m1, m2, m3)$`Pr(>Chisq)`
+  expect_equal(p, rez$p, tolerance = 1e-03)
+
+  rez <- test_likelihoodratio(m3, m2, m1, estimator = "ML")
+  p <- c(NA, 0.4747344, 0.5302030) # lmtest::lrtest(m3, m2, m1)$`Pr(>Chisq)`
+  expect_equal(p, rez$p, tolerance = 1e-03)
+})
+
+test_that("test_likelihoodratio - model names", {
+  m1 <- lm(mpg ~ wt + cyl + gear + disp, data = mtcars)
+  m2 <- lm(mpg ~ wt + cyl + gear, data = mtcars)
+  m3 <- lm(mpg ~ wt + cyl, data = mtcars)
+
+  rez <- test_likelihoodratio(m1, m2, m3)
+  expect_equal(rez$Name, c("m1", "m2", "m3"))
+
+  rez <- test_likelihoodratio(list(m1, m2, m3))
+  expect_equal(rez$Name, c("Model 1", "Model 2", "Model 3"))
+
+  models <- list(m1, m2, m3)
+  rez <- test_likelihoodratio(models)
+  expect_equal(rez$Name, c("Model 1", "Model 2", "Model 3"))
+})
+
+test_that("test_likelihoodratio - reversed order", {
+  m1 <- lm(mpg ~ wt + cyl, data = mtcars)
+  m2 <- lm(mpg ~ wt + cyl + gear, data = mtcars)
+  m3 <- lm(mpg ~ wt + cyl + gear + disp, data = mtcars)
+
+  rez <- test_likelihoodratio(m1, m2, m3, estimator = "OLS")
+  ref <- anova(m1, m2, m3, test = "LRT")
+  expect_equal(ref$`Pr(>Chi)`, rez$p, tolerance = 1e-03)
+
+  rez <- test_likelihoodratio(m1, m2, m3, estimator = "ML")
+  p <- c(NA, 0.4747344, 0.5302030) # lmtest::lrtest(m1, m2, m3)$`Pr(>Chisq)`
+  expect_equal(p, rez$p, tolerance = 1e-03)
+})
+
+.runThisTest <- Sys.getenv("RunAllperformanceTests") == "yes"
+
+if (.runThisTest && requiet("lme4")) {
+  m1 <- lmer(Sepal.Length ~ Petal.Width + (1 | Species), data = iris)
+  m2 <- lmer(Sepal.Length ~ Petal.Width + Petal.Length + (1 | Species), data = iris)
+  m3 <- lmer(Sepal.Length ~ Petal.Width * Petal.Length + (1 | Species), data = iris)
+
+  test_that("test_likelihoodratio - lme4 ML", {
+    t1 <- test_lrt(m1, m2, m3)
+    t2 <- anova(m1, m2, m3)
+    expect_equal(attributes(t1)$estimator, "ml")
+    expect_equal(t1$Chi2, c(NA, 85.26365, 0.84141), tolerance = 1e-3)
+    expect_equal(t1$p, c(NA, 0, 0.35899), tolerance = 1e-3)
+    # close, but not the same
+    expect_equal(t1$p, t2$`Pr(>Chisq)`, tolerance = 1e-1)
+    expect_equal(t1$Chi2, t2$Chisq, tolerance = 1e-1)
   })
 
-  test_that("test_likelihoodratio - model names", {
-    m1 <- lm(mpg ~ wt + cyl + gear + disp, data = mtcars)
-    m2 <- lm(mpg ~ wt + cyl + gear, data = mtcars)
-    m3 <- lm(mpg ~ wt + cyl, data = mtcars)
+  test_that("test_likelihoodratio - lme4 OLS", {
+    t2 <- test_lrt(m1, m2, m3, estimator = "ols")
+    expect_equal(attributes(t2)$estimator, "ols")
+    expect_equal(t2$Chi2, c(NA, 105.73844, 1.04346), tolerance = 1e-3)
+    expect_equal(t2$p, c(NA, 0, 0.30702), tolerance = 1e-3)
+  })
 
-    rez <- test_likelihoodratio(m1, m2, m3)
-    expect_equal(rez$Name, c("m1", "m2", "m3"))
+  test_that("test_likelihoodratio - lme4 REML", {
+    expect_warning(t3 <- test_lrt(m1, m2, m3, estimator = "REML"))
+    expect_equal(attributes(t3)$estimator, "reml")
+    expect_equal(t3$Chi2, c(NA, 89.32933, 2.85635), tolerance = 1e-3)
+    expect_equal(t3$p, c(NA, 0, 0.09101), tolerance = 1e-3)
+  })
 
-    rez <- test_likelihoodratio(list(m1, m2, m3))
-    expect_equal(rez$Name, c("Model 1", "Model 2", "Model 3"))
+  m1 <- glm(am ~ mpg, data = mtcars, family = binomial())
+  m2 <- glm(am ~ mpg + hp, data = mtcars, family = binomial())
+  m3 <- glm(am ~ mpg + hp + vs, data = mtcars, family = binomial())
 
-    models <- list(m1, m2, m3)
-    rez <- test_likelihoodratio(models)
-    expect_equal(rez$Name, c("Model 1", "Model 2", "Model 3"))
+  test_that("test_likelihoodratio - glm", {
+    t1 <- anova(m1, m2, m3, test = "LRT")
+    t2 <- test_lrt(m1, m2, m3)
+    expect_equal(t1$`Pr(>Chi)`, t2$p, tolerance = 1e-3)
+    expect_equal(t1$Deviance, t2$Chi2, tolerance = 1e-3)
+    expect_equal(attributes(t2)$estimator, "ml")
   })
 
-  test_that("test_likelihoodratio - reversed order", {
-    m1 <- lm(mpg ~ wt + cyl, data = mtcars)
-    m2 <- lm(mpg ~ wt + cyl + gear, data = mtcars)
-    m3 <- lm(mpg ~ wt + cyl + gear + disp, data = mtcars)
+  m1 <- lm(Sepal.Length ~ Petal.Width, data = iris)
+  m2 <- lm(Sepal.Length ~ Petal.Width + Species, data = iris)
+  m3 <- lm(Sepal.Length ~ Petal.Width * Species, data = iris)
 
-    rez <- test_likelihoodratio(m1, m2, m3, estimator = "OLS")
-    ref <- anova(m1, m2, m3, test = "LRT")
-    expect_equal(ref$`Pr(>Chi)`, rez$p, tolerance = 1e-03)
-
-    rez <- test_likelihoodratio(m1, m2, m3, estimator = "ML")
-    p <- c(NA, 0.4747344, 0.5302030) # lmtest::lrtest(m1, m2, m3)$`Pr(>Chisq)`
-    expect_equal(p, rez$p, tolerance = 1e-03)
+  test_that("test_likelihoodratio - lm", {
+    t1 <- anova(m1, m2, m3, test = "LRT")
+    t2 <- test_lrt(m1, m2, m3)
+    expect_equal(t1$`Pr(>Chi)`, t2$p, tolerance = 1e-3)
+    expect_equal(attributes(t2)$estimator, "ols")
   })
-
-  .runThisTest <- Sys.getenv("RunAllperformanceTests") == "yes"
-
-  if (.runThisTest && requiet("lme4")) {
-    m1 <- lmer(Sepal.Length ~ Petal.Width + (1 | Species), data = iris)
-    m2 <- lmer(Sepal.Length ~ Petal.Width + Petal.Length + (1 | Species), data = iris)
-    m3 <- lmer(Sepal.Length ~ Petal.Width * Petal.Length + (1 | Species), data = iris)
-
-    test_that("test_likelihoodratio - lme4 ML", {
-      t1 <- test_lrt(m1, m2, m3)
-      t2 <- anova(m1, m2, m3)
-      expect_equal(attributes(t1)$estimator, "ml")
-      expect_equal(t1$Chi2, c(NA, 85.26365, 0.84141), tolerance = 1e-3)
-      expect_equal(t1$p, c(NA, 0, 0.35899), tolerance = 1e-3)
-      # close, but not the same
-      expect_equal(t1$p, t2$`Pr(>Chisq)`, tolerance = 1e-1)
-      expect_equal(t1$Chi2, t2$Chisq, tolerance = 1e-1)
-    })
-
-    test_that("test_likelihoodratio - lme4 OLS", {
-      t2 <- test_lrt(m1, m2, m3, estimator = "ols")
-      expect_equal(attributes(t2)$estimator, "ols")
-      expect_equal(t2$Chi2, c(NA, 105.73844, 1.04346), tolerance = 1e-3)
-      expect_equal(t2$p, c(NA, 0, 0.30702), tolerance = 1e-3)
-    })
-
-    test_that("test_likelihoodratio - lme4 REML", {
-      expect_warning(t3 <- test_lrt(m1, m2, m3, estimator = "REML"))
-      expect_equal(attributes(t3)$estimator, "reml")
-      expect_equal(t3$Chi2, c(NA, 89.32933, 2.85635), tolerance = 1e-3)
-      expect_equal(t3$p, c(NA, 0, 0.09101), tolerance = 1e-3)
-    })
-
-    m1 <- glm(am ~ mpg, data = mtcars, family = binomial())
-    m2 <- glm(am ~ mpg + hp, data = mtcars, family = binomial())
-    m3 <- glm(am ~ mpg + hp + vs, data = mtcars, family = binomial())
-
-    test_that("test_likelihoodratio - glm", {
-      t1 <- anova(m1, m2, m3, test = "LRT")
-      t2 <- test_lrt(m1, m2, m3)
-      expect_equal(t1$`Pr(>Chi)`, t2$p, tolerance = 1e-3)
-      expect_equal(t1$Deviance, t2$Chi2, tolerance = 1e-3)
-      expect_equal(attributes(t2)$estimator, "ml")
-    })
-
-    m1 <- lm(Sepal.Length ~ Petal.Width, data = iris)
-    m2 <- lm(Sepal.Length ~ Petal.Width + Species, data = iris)
-    m3 <- lm(Sepal.Length ~ Petal.Width * Species, data = iris)
-
-    test_that("test_likelihoodratio - lm", {
-      t1 <- anova(m1, m2, m3, test = "LRT")
-      t2 <- test_lrt(m1, m2, m3)
-      expect_equal(t1$`Pr(>Chi)`, t2$p, tolerance = 1e-3)
-      expect_equal(attributes(t2)$estimator, "ols")
-    })
-  }
 }
diff --git a/tests/testthat/test-test_wald.R b/tests/testthat/test-test_wald.R
index df11be538..34ecb0ea8 100644
--- a/tests/testthat/test-test_wald.R
+++ b/tests/testthat/test-test_wald.R
@@ -1,43 +1,37 @@
-if (requiet("testthat") &&
-  requiet("performance") &&
-  requiet("lavaan") &&
-  requiet("lmtest")) {
-  test_that("test_wald - lm", {
-    m1 <- lm(Sepal.Length ~ Petal.Width * Species, data = iris)
-    m2 <- lm(Sepal.Length ~ Petal.Width + Species, data = iris)
-    m3 <- lm(Sepal.Length ~ Petal.Width, data = iris)
-
-    rez <- test_wald(m1, m2, m3)
-    ref <- as.data.frame(anova(m1, m2, m3))
-
-    expect_equal(rez$`F`, ref$`F`)
-    expect_equal(rez$p, ref$`Pr(>F)`)
-
-    # setting test = "LRT" is not expected, but should at least not fail
-    expect_warning(rez <- test_wald(m1, m2, test = "LRT"))
-    expect_equal(rez$Name, c("..1", "..2"))
-
-    # Reversed
-    m3 <- m1
-    m1 <- lm(Sepal.Length ~ Petal.Width, data = iris)
-
-    rez <- test_wald(m1, m2, m3)
-    ref <- as.data.frame(anova(m1, m2, m3))
-
-    expect_equal(rez$`F`, ref$`F`)
-    expect_equal(rez$p, ref$`Pr(>F)`)
-  })
-
-  test_that("test_wald - glm", {
-    m1 <- glm(vs ~ disp + hp + drat, data = mtcars, family = "binomial")
-    m2 <- glm(vs ~ disp + hp, data = mtcars, family = "binomial")
-    m3 <- glm(vs ~ disp, data = mtcars, family = "binomial")
-
-    rez <- test_wald(m1, m2, m3)
-    # Why different?
-    # ref <- lmtest::waldtest(m1, m2, m3)
-    #
-    # expect_equal(rez$`F`, ref$`F`)
-    # expect_equal(rez$p, ref$`Pr(>F)`)
-  })
-}
+test_that("test_wald - lm", {
+  m1 <- lm(Sepal.Length ~ Petal.Width * Species, data = iris)
+  m2 <- lm(Sepal.Length ~ Petal.Width + Species, data = iris)
+  m3 <- lm(Sepal.Length ~ Petal.Width, data = iris)
+
+  rez <- test_wald(m1, m2, m3)
+  ref <- as.data.frame(anova(m1, m2, m3))
+
+  expect_equal(rez$`F`, ref$`F`, tolerance = 1e-4)
+  expect_equal(rez$p, ref$`Pr(>F)`, tolerance = 1e-4)
+
+  # setting test = "LRT" is not expected, but should at least not fail
+  expect_warning(rez <- test_wald(m1, m2, test = "LRT"))
+  expect_equal(rez$Name, c("..1", "..2"))
+
+  # Reversed
+  m3 <- m1
+  m1 <- lm(Sepal.Length ~ Petal.Width, data = iris)
+
+  rez <- test_wald(m1, m2, m3)
+  ref <- as.data.frame(anova(m1, m2, m3))
+
+  expect_equal(rez$`F`, ref$`F`, tolerance = 1e-4)
+  expect_equal(rez$p, ref$`Pr(>F)`, tolerance = 1e-4)
+})
+
+test_that("test_wald - glm", {
+  m1 <- glm(vs ~ disp + hp + drat, data = mtcars, family = "binomial")
+  m2 <- glm(vs ~ disp + hp, data = mtcars, family = "binomial")
+  m3 <- glm(vs ~ disp, data = mtcars, family = "binomial")
+
+  expect_warning(rez <- test_wald(m1, m2, m3))
+  ref <- as.data.frame(anova(m1, m2, m3, test = "LRT"))
+
+  expect_equal(rez$Chi2, abs(ref$Deviance), tolerance = 1e-4)
+  expect_equal(rez$p, ref$`Pr(>Chi)`, tolerance = 1e-4)
+})