#library(testthat)
library(MANOVA.RM)
context("MANOVA output")
test_that("MANOVA type",{
data(EEG)
mod1 <- MANOVA(resp ~ sex * diagnosis, data = EEG,
subject = "id", iter = 10, CPU = 1)
expect_is(mod1, "MANOVA")
})
test_that("example 1: one-way",{
mod <- MANOVA(resp ~ diagnosis, data = EEG, subject = "id", iter = 10, CPU = 1)
names(mod$WTS) <- NULL
expect_equal(mod$WTS[1], 53.553)
})
test_that("example 2: two-way",{
mod <- MANOVA(resp ~ sex * diagnosis, data = EEG, subject = "id", iter = 10, CPU = 1)
names(mod$WTS) <- NULL
expect_equal(mod$WTS[1], 12.604)
})
test_that("example 3: three-way",{
expect_warning(mod <- MANOVA(resp ~ sex * diagnosis * age, data = EEG, subject = "id",
iter = 10, CPU = 1))
names(mod$WTS) <- NULL
expect_equal(mod$WTS[1], 28.874)
})
test_that("example 4: nested design",{
if(requireNamespace("GFD")){
library(GFD)
data(curdies)
set.seed(123)
curdies$dug2 <- curdies$dugesia + rnorm(36)
mod <- MANOVA.wide(cbind(dugesia, dug2) ~ season + season:site, data = curdies, iter = 10,
nested.levels.unique = TRUE, CPU = 1)
names(mod$WTS) <- NULL
expect_equal(mod$WTS[1], 6.999)
}
})
test_that("singular covariance matrix", {
expect_warning(test <- MANOVA(resp ~ diagnosis*sex*age, data = EEG, iter = 10, subject = "id", CPU = 1))
})
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