skip_on_os(c("mac", "linux", "solaris"))
skip_if_not_installed("brglm2")
skip_if_not_installed("MASS")
skip_if_not_installed("nnet")
test_that("print ggpredict ordinal outcome", {
data("stemcell", package = "brglm2")
m_bracl <- brglm2::bracl(research ~ as.numeric(religion) + gender,
weights = frequency,
data = stemcell, type = "ML"
)
m_polr <- MASS::polr(research ~ as.numeric(religion) + gender,
weights = frequency,
data = stemcell
)
m_nnet <- nnet::multinom(research ~ as.numeric(religion) + gender,
weights = frequency,
data = stemcell
)
out1 <- ggpredict(m_bracl, "gender")
out2 <- ggpredict(m_polr, "gender")
out3 <- ggpredict(m_nnet, "gender")
expect_equal(out1$predicted, out2$predicted, tolerance = 0.05)
expect_equal(out1$predicted, out3$predicted, tolerance = 0.05)
out4 <- predict_response(m_bracl, "gender", margin = "empirical")
out5 <- predict_response(m_polr, "gender", margin = "empirical")
out6 <- predict_response(m_nnet, "gender", margin = "empirical")
expect_named(
out4,
c(
"x", "predicted", "std.error", "conf.low", "conf.high", "response.level",
"group"
)
)
expect_equal(as.character(out4$response.level), out1$response.level, ignore_attr = TRUE)
expect_equal(out4$predicted, out6$predicted, tolerance = 0.05)
expect_equal(out5$predicted, c(
0.30221, 0.44275, 0.1502, 0.10484, 0.29403, 0.44341, 0.15392,
0.10863
), tolerance = 0.05)
})
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