Nothing
skip_if_not_installed("glmmTMB")
test_that("report.glmmTMB", {
skip_on_cran() # glmmTMB models can be computationally intensive
# Create a simple dataset for testing
set.seed(123)
data_test <- data.frame(
y = rpois(100, lambda = 2),
x = rnorm(100),
group = factor(rep(1:10, 10))
)
# Create a simple glmmTMB model
suppressWarnings({
model <- glmmTMB::glmmTMB(
y ~ x + (1 | group),
data = data_test,
family = poisson()
)
})
# Test main report function
r <- report(model)
expect_s3_class(r, "report")
expect_s3_class(summary(r), "character")
expect_s3_class(as.data.frame(r), c("report_table", "data.frame"))
# Test that basic structure is correct
expect_gt(nchar(summary(r)), 0)
expect_gt(nrow(as.data.frame(r)), 0)
# Test report components
rt <- report_table(model)
expect_s3_class(rt, c("report_table", "data.frame"))
expect_true("Parameter" %in% names(rt))
# Test that random effects are reported
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))
})
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