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skip_if_not_installed("boot")
test_that("model_parameters.lm", {
model <- lm(mpg ~ wt, data = mtcars)
params <- model_parameters(model, verbose = FALSE)
expect_identical(c(nrow(params), ncol(params)), c(2L, 9L))
expect_equal(params$CI_high, c(41.119752761418, -4.20263490802709), tolerance = 1e-3)
expect_equal(attributes(params)$sigma, 3.045882, tolerance = 1e-3)
params <- model_parameters(model, ci = c(0.8, 0.9), verbose = FALSE)
expect_identical(c(nrow(params), ncol(params)), c(2L, 10L))
params <- model_parameters(model, dispersion = TRUE, bootstrap = TRUE, iterations = 500, verbose = FALSE)
expect_identical(c(nrow(params), ncol(params)), c(2L, 7L))
model <- lm(mpg ~ wt + cyl, data = mtcars)
params <- model_parameters(model, verbose = FALSE)
expect_identical(c(nrow(params), ncol(params)), c(3L, 9L))
model <- lm(mpg ~ wt * cyl, data = mtcars)
params <- model_parameters(model, verbose = FALSE)
expect_identical(c(nrow(params), ncol(params)), c(4L, 9L))
params <- model_parameters(model, component = "conditional", effects = "fixed", verbose = FALSE)
})
test_that("print digits model_parameters.lm", {
model <- lm(mpg ~ wt, data = mtcars)
params <- model_parameters(model, digits = 4, ci_digits = 5, verbose = FALSE)
out <- capture.output(print(params))
expect_identical(out[3], "(Intercept) | 37.2851 | 1.8776 | [33.45050, 41.11975] | 19.8576 | < .001")
})
test_that("print digits model_parameters.lm", {
skip_if_not_installed("performance")
model <- lm(mpg ~ wt, data = mtcars)
params <- model_parameters(model, include_info = TRUE, verbose = FALSE)
expect_snapshot(params)
params <- model_parameters(model, include_info = FALSE, verbose = FALSE)
expect_snapshot(params)
})
test_that("model_parameters.glm - binomial", {
set.seed(333)
model <- glm(vs ~ wt + cyl, data = mtcars, family = "binomial")
params <- model_parameters(model, verbose = FALSE)
expect_identical(c(nrow(params), ncol(params)), c(3L, 9L))
params <- suppressWarnings(model_parameters(model, bootstrap = TRUE, iterations = 500, verbose = FALSE))
expect_identical(c(nrow(params), ncol(params)), c(3L, 6L))
params <- model_parameters(model, component = "conditional", effects = "fixed", verbose = FALSE)
})
test_that("model_parameters.glm - Gamma - print", {
# test printing for prevalence ratios
clotting <- data.frame(
u = c(5, 10, 15, 20, 30, 40, 60, 80, 100),
lot1 = c(118, 58, 42, 35, 27, 25, 21, 19, 18),
lot2 = c(69, 35, 26, 21, 18, 16, 13, 12, 12)
)
m <- glm(lot1 ~ log(u), data = clotting, family = Gamma("log"))
mp <- model_parameters(m, exponentiate = TRUE)
expect_snapshot(mp)
})
test_that("model_parameters.glm - glm, identity link", {
data(mtcars)
m <- glm(am ~ vs, data = mtcars, family = binomial(link = "identity"))
p <- model_parameters(m)
expect_identical(attributes(p)$coefficient_name, "Risk")
})
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