easystats · rempsyc · Sep 22, 2025 · Sep 22, 2025 · Sep 22, 2025 · Sep 22, 2025
diff --git a/NEWS.md b/NEWS.md
@@ -10,6 +10,7 @@ Bug fixes
 
 Minor changes
 * Fixed a lot of linting issues across the package.
+* Increased test coverage across the package.
 
 # report 0.6.1
 

diff --git a/tests/testthat/test-coverage-MixMod.R b/tests/testthat/test-coverage-MixMod.R
@@ -0,0 +1,55 @@
+# Coverage tests for report.MixMod functions
+
+skip_if_not_installed("GLMMadaptive")
+
+test_that("report.MixMod coverage test", {
+  set.seed(999)
+  # Create longitudinal data suitable for GLMMadaptive
+  n_subjects <- 8
+  n_timepoints <- 4
+
+  data_mixmod <- data.frame(
+    id = rep(1:n_subjects, each = n_timepoints),
+    time = rep(c(0, 1, 2, 3), n_subjects),
+    x = rnorm(n_subjects * n_timepoints)
+  )
+
+  # Create binary outcome appropriate for GLMMadaptive
+  data_mixmod$y <- rbinom(
+    nrow(data_mixmod), 1,
+    plogis(-1 + 0.5 * data_mixmod$time + 0.3 * data_mixmod$x)
+  )
+
+  # Create GLMMadaptive mixed model
+  suppressWarnings({
+    model <- GLMMadaptive::mixed_model(
+      fixed = y ~ time + x,
+      random = ~ 1 | id,
+      data = data_mixmod,
+      family = binomial()
+    )
+  })
+
+  # Test report.MixMod (which is aliased to report.lm)
+  r <- suppressWarnings(report(model, data = data_mixmod))
+  expect_s3_class(r, "report")
+  expect_type(summary(r), "character")
+  expect_s3_class(as.data.frame(r), c("report_table", "data.frame"))
+
+  # Test report_random.MixMod specifically
+  rr <- report_random(model)
+  expect_s3_class(rr, c("report_random", "character"))
+  expect_true(grepl("random effect", rr, fixed = TRUE))
+
+  # Test other MixMod-specific functions for coverage
+  rt <- report_table(model)
+  expect_s3_class(rt, c("report_table", "data.frame"))
+
+  # Test report_performance for MixMod
+  rp <- suppressWarnings(report_performance(model))
+  expect_s3_class(rp, c("report_performance", "character"))
+
+  # Test report_effectsize for MixMod
+  re <- suppressWarnings(report_effectsize(model))
+  expect_s3_class(re, "report_effectsize")
+})
diff --git a/tests/testthat/test-coverage-brmsfit.R b/tests/testthat/test-coverage-brmsfit.R
@@ -0,0 +1,76 @@
+# Coverage tests for report.brmsfit functions
+# These are minimal tests to ensure coverage of functions that might be skipped in CI
+
+skip_if_not_installed("brms")
+
+test_that("report.brmsfit coverage test", {
+  # Create a very simple brms model for testing
+  # Use minimal iterations and very simple data to make it fast
+  skip_if_not_installed("rstanarm") # often needed for brms
+
+  set.seed(42)
+  # Use a tiny dataset to make model fitting very fast
+  tiny_data <- data.frame(
+    y = rnorm(10, mean = 2),
+    x = rnorm(10)
+  )
+
+  # Create minimal brms model with very few iterations
+  suppressMessages(suppressWarnings({
+    model <- brms::brm(
+      y ~ x,
+      data = tiny_data,
+      refresh = 0,
+      iter = 100, # Very small number for speed
+      chains = 1, # Single chain for speed
+      seed = 42,
+      silent = 2 # Suppress output
+    )
+  }))
+
+  # Test the main report function (coverage for report.brmsfit)
+  r <- suppressWarnings(report(model, verbose = FALSE))
+  expect_s3_class(r, "report")
+  expect_type(summary(r), "character")
+  expect_s3_class(as.data.frame(r), "data.frame")
+
+  # Test report_effectsize.brmsfit coverage
+  r_eff <- suppressWarnings(report_effectsize(model))
+  expect_s3_class(r_eff, "report_effectsize")
+
+  # Test report_priors.brmsfit coverage - this might return empty for default priors
+  r_priors <- suppressWarnings(report_priors(model))
+  expect_type(r_priors, "character")
+})
+
+test_that("report_priors.brmsfit with explicit priors coverage", {
+  skip_if_not_installed("brms")
+  skip_if_not_installed("rstanarm")
+
+  set.seed(123)
+  tiny_data <- data.frame(
+    y = rnorm(8, mean = 1),
+    x = rnorm(8)
+  )
+
+  # Create model with explicit priors to test prior reporting
+  suppressMessages(suppressWarnings({
+    model_with_priors <- brms::brm(
+      y ~ x,
+      data = tiny_data,
+      prior = c(
+        brms::prior(normal(0, 1), class = Intercept),
+        brms::prior(normal(0, 0.5), class = b)
+      ),
+      refresh = 0,
+      iter = 50, # Even fewer iterations
+      chains = 1,
+      seed = 123,
+      silent = 2
+    )
+  }))
+
+  # Test report_priors with actual priors
+  r_priors <- suppressWarnings(report_priors(model_with_priors))
+  expect_type(r_priors, "character")
+})
diff --git a/tests/testthat/test-coverage-compare-loo.R b/tests/testthat/test-coverage-compare-loo.R
@@ -0,0 +1,64 @@
+# Coverage tests for report.compare.loo function
+
+skip_if_not_installed("brms")
+skip_if_not_installed("loo")
+
+test_that("report.compare.loo coverage test", {
+  skip_if_not_installed("rstanarm")
+
+  set.seed(456)
+  # Create minimal dataset
+  tiny_data <- data.frame(
+    y = rnorm(12, mean = 3),
+    x1 = rnorm(12),
+    x2 = rnorm(12)
+  )
+
+  # Create two very simple models for comparison
+  suppressMessages(suppressWarnings({
+    m1 <- brms::brm(
+      y ~ x1,
+      data = tiny_data,
+      refresh = 0,
+      iter = 50,
+      chains = 1,
+      seed = 456,
+      silent = 2
+    )
+
+    m2 <- brms::brm(
+      y ~ x1 + x2,
+      data = tiny_data,
+      refresh = 0,
+      iter = 50,
+      chains = 1,
+      seed = 456,
+      silent = 2
+    )
+  }))
+
+  # Add LOO criterion (this is what creates compare.loo objects)
+  suppressWarnings({
+    m1 <- brms::add_criterion(m1, "loo")
+    m2 <- brms::add_criterion(m2, "loo")
+  })
+
+  # Create model comparison object
+  comparison <- suppressWarnings(brms::loo_compare(
+    m1, m2,
+    model_names = c("model1", "model2")
+  ))
+
+  # Test report.compare.loo function
+  r <- report(comparison)
+  expect_s3_class(r, c("report_text", "character"))
+  expect_gt(nchar(r), 0)
+  expect_true(grepl("ELPD", r, fixed = TRUE))
+
+  # Test with different parameters
+  r2 <- report(comparison, include_IC = FALSE)
+  expect_s3_class(r2, c("report_text", "character"))
+
+  r3 <- report(comparison, include_ENP = TRUE)
+  expect_s3_class(r3, c("report_text", "character"))
+})
diff --git a/tests/testthat/test-coverage-glmmTMB.R b/tests/testthat/test-coverage-glmmTMB.R
@@ -0,0 +1,47 @@
+# Coverage tests for report.glmmTMB functions
+
+skip_if_not_installed("glmmTMB")
+
+test_that("report.glmmTMB coverage test", {
+  set.seed(789)
+  # Create simple test data
+  test_data <- data.frame(
+    y = rpois(20, lambda = 1.5),
+    x = rnorm(20),
+    group = factor(rep(1:4, 5))
+  )
+
+  # Create minimal glmmTMB model
+  suppressWarnings({
+    model <- glmmTMB::glmmTMB(
+      y ~ x + (1 | group),
+      data = test_data,
+      family = poisson()
+    )
+  })
+
+  # Test report.glmmTMB (which is aliased to report.lm)
+  r <- report(model)
+  expect_s3_class(r, "report")
+  expect_type(summary(r), "character")
+  expect_s3_class(as.data.frame(r), c("report_table", "data.frame"))
+
+  # Test report_random.glmmTMB specifically
+  rr <- report_random(model)
+  expect_s3_class(rr, c("report_random", "character"))
+  expect_true(grepl("random effect", rr, fixed = TRUE))
+  expect_true(grepl("group", rr, fixed = TRUE))
+
+  # Test other glmmTMB-specific functions for coverage
+  rt <- report_table(model)
+  expect_s3_class(rt, c("report_table", "data.frame"))
+  expect_true("Parameter" %in% names(rt))
+
+  # Test report_performance for glmmTMB
+  rp <- report_performance(model)
+  expect_s3_class(rp, c("report_performance", "character"))
+
+  # Test report_effectsize for glmmTMB
+  re <- suppressWarnings(report_effectsize(model))
+  expect_s3_class(re, "report_effectsize")
+})