context("test-lme4")
# Read test results
test_results <- read_stats("test_results.csv")
# Run tests, consisting of the following steps:
# - Retrieve the correct output from the test results file
# - Run the statistical model
# - Tidy the output
# - Compare the tidied output with the (correct) output from the file
test_that("lme4's linear mixed models work", {
correct <- test_results[["lme4_lme"]]
model <- lme4::lmer(Reaction ~ Days + (Days | Subject), lme4::sleepstudy)
output <- tidy_stats(model)
expect_equal(as.data.frame(output), as.data.frame(correct), tolerance = .002)
})
test_that("lme4's linear mixed models with uncorrelated terms work", {
correct <- test_results[["lme4_lme_uncorrelated"]]
model <- lme4::lmer(Reaction ~ Days + (Days || Subject), lme4::sleepstudy)
output <- tidy_stats(model)
expect_equal(as.data.frame(output), as.data.frame(correct), tolerance = .002)
})
test_that("lme4's linear mixed models with dummies work", {
correct <- test_results[["lme4_lme_dummies"]]
data(Orthodont, package = "nlme")
Orthodont$nsex <- as.numeric(Orthodont$Sex == "Male")
Orthodont$nsexage <- with(Orthodont, nsex * age)
model <- lme4::lmer(distance ~ age + (age|Subject) + (0 + nsex|Subject) +
(0 + nsexage|Subject), data = Orthodont)
output <- tidy_stats(model)
expect_equal(as.data.frame(output), as.data.frame(correct), tolerance = .002)
})
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