skip_on_os("linux")
test_that("p_direction", {
skip_if_not_or_load_if_installed("BayesFactor")
set.seed(333)
x <- BayesFactor::correlationBF(y = iris$Sepal.Length, x = iris$Sepal.Width)
expect_equal(as.numeric(p_direction(x)), 0.9225, tolerance = 1)
})
test_that("p_direction: BF t.test one sample", {
skip_if_not_or_load_if_installed("BayesFactor")
data(sleep)
diffScores <- sleep$extra[1:10] - sleep$extra[11:20]
x <- BayesFactor::ttestBF(x = diffScores)
expect_equal(as.numeric(p_direction(x)), 0.99675, tolerance = 1)
})
test_that("p_direction: BF t.test two samples", {
skip_if_not_or_load_if_installed("BayesFactor")
data(chickwts)
chickwts <- chickwts[chickwts$feed %in% c("horsebean", "linseed"), ]
chickwts$feed <- factor(chickwts$feed)
x <- BayesFactor::ttestBF(formula = weight ~ feed, data = chickwts)
expect_equal(as.numeric(p_direction(x)), 1, tolerance = 1)
})
test_that("p_direction: BF t.test meta-analytic", {
skip_if_not_or_load_if_installed("BayesFactor")
t <- c(-0.15, 2.39, 2.42, 2.43)
N <- c(100, 150, 97, 99)
x <- BayesFactor::meta.ttestBF(t = t, n1 = N, rscale = 1)
expect_equal(as.numeric(p_direction(x)), 0.99975, tolerance = 1)
})
skip_if_not_or_load_if_installed("BayesFactor")
# ---------------------------
# "BF ANOVA"
data(ToothGrowth)
ToothGrowth$dose <- factor(ToothGrowth$dose)
levels(ToothGrowth$dose) <- c("Low", "Medium", "High")
x <- BayesFactor::anovaBF(len ~ supp * dose, data = ToothGrowth)
test_that("p_direction", {
expect_equal(as.numeric(p_direction(x)), c(1, 0.95675, 0.95675, 1, 1), tolerance = 0.1)
})
# BF ANOVA Random ---------------------------
data(puzzles)
x <- BayesFactor::anovaBF(RT ~ shape * color + ID, data = puzzles, whichRandom = "ID")
test_that("p_direction", {
expect_equal(as.numeric(p_direction(x)), c(
1, 0.98125, 0.98125, 0.995, 0.67725, 0.8285, 0.68425, 0.99975,
0.6725, 0.9995, 0.60275, 0.99525, 0.7615, 0.763, 1, 1, 1, 1
), tolerance = 0.1)
})
# ---------------------------
# "BF lm"
x <- BayesFactor::lmBF(len ~ supp + dose, data = ToothGrowth)
test_that("p_direction", {
expect_equal(as.numeric(p_direction(x)), c(1, 0.9995, 0.9995, 1, 0.903, 1, 1, 1, 1), tolerance = 0.1)
})
x2 <- BayesFactor::lmBF(len ~ supp + dose + supp:dose, data = ToothGrowth)
x <- x / x2
test_that("p_direction", {
expect_equal(as.numeric(p_direction(x)), c(1, 0.99925, 0.99925, 1, 0.89975, 1, 1, 1, 1), tolerance = 0.1)
})
test_that("rope_range", {
skip_if_not_or_load_if_installed("BayesFactor")
x <- BayesFactor::lmBF(len ~ supp + dose, data = ToothGrowth)
expect_equal(rope_range(x)[2], sd(ToothGrowth$len) / 10, tolerance = 1e-4)
x <- BayesFactor::ttestBF(
ToothGrowth$len[ToothGrowth$supp == "OJ"],
ToothGrowth$len[ToothGrowth$supp == "VC"]
)
expect_equal(rope_range(x)[2], sd(ToothGrowth$len) / 10, tolerance = 1e-4)
x <- BayesFactor::ttestBF(formula = len ~ supp, data = ToothGrowth)
expect_equal(rope_range(x)[2], sd(ToothGrowth$len) / 10, tolerance = 1e-4)
# else
x <- BayesFactor::correlationBF(ToothGrowth$len, as.numeric(ToothGrowth$dose))
expect_equal(rope_range(x, verbose = FALSE), c(-0.05, 0.05), tolerance = 1e-4)
})
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