Nothing
skip_on_cran()
skip_if_not_installed("glmmTMB")
skip_if_not_installed("MuMIn")
skip_if_not_installed("lme4")
skip_if_not_installed("performance", minimum_version = "0.12.1")
# ==============================================================================
# Binomial mixed models, lme4 ----
# ==============================================================================
test_that("lme4, binomial", {
# dataset
data(cbpp, package = "lme4")
# lme4, no random slope ----------------------------------------------------
m <- lme4::glmer(
cbind(incidence, size - incidence) ~ period + (1 | herd),
data = cbpp,
family = binomial()
)
out1 <- suppressWarnings(MuMIn::r.squaredGLMM(m))
out2 <- performance::r2_nakagawa(m)
# matches theoretical values
expect_equal(out1[1, "R2m"], out2$R2_marginal, ignore_attr = TRUE, tolerance = 1e-3)
expect_equal(out1[1, "R2c"], out2$R2_conditional, ignore_attr = TRUE, tolerance = 1e-3)
})
# ==============================================================================
# Binomial mixed models, glmmTMB ----
# ==============================================================================
test_that("glmmTMB, binomial", {
# dataset
data(cbpp, package = "lme4")
# lme4, no random slope ----------------------------------------------------
m <- glmmTMB::glmmTMB(
cbind(incidence, size - incidence) ~ period + (1 | herd),
data = cbpp,
family = binomial()
)
out1 <- suppressWarnings(MuMIn::r.squaredGLMM(m))
out2 <- performance::r2_nakagawa(m)
# matches theoretical values
expect_equal(out1[1, "R2m"], out2$R2_marginal, ignore_attr = TRUE, tolerance = 1e-3)
expect_equal(out1[1, "R2c"], out2$R2_conditional, ignore_attr = TRUE, tolerance = 1e-3)
})
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