if (require("testthat") && require("BayesFactor") && require("bayestestR")) { set.seed(333) x <- BayesFactor::correlationBF(y = iris$Sepal.Length, x = iris$Sepal.Width) test_that("p_direction", { expect_equal(as.numeric(p_direction(x)), 0.9225, tol = 1) }) # BF t.test one sample --------------------------- data(sleep) diffScores <- sleep$extra[1:10] - sleep$extra[11:20] x <- BayesFactor::ttestBF(x = diffScores) test_that("p_direction", { expect_equal(as.numeric(p_direction(x)), 0.99675, tol = 1) }) # BF t.test two samples --------------------------- data(chickwts) chickwts <- chickwts[chickwts$feed %in% c("horsebean", "linseed"), ] chickwts$feed <- factor(chickwts$feed) x <- BayesFactor::ttestBF(formula = weight ~ feed, data = chickwts) test_that("p_direction", { expect_equal(as.numeric(p_direction(x)), 1, tol = 1) }) # BF t.test meta-analytic --------------------------- t <- c(-.15, 2.39, 2.42, 2.43) N <- c(100, 150, 97, 99) x <- BayesFactor::meta.ttestBF(t = t, n1 = N, rscale = 1) test_that("p_direction", { expect_equal(as.numeric(p_direction(x)), 0.99975, tol = 1) }) # # --------------------------- # context("BF ANOVA") # data(ToothGrowth) # ToothGrowth$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)), 91.9, tol=0.1) # }) # # # --------------------------- # context("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)), 91.9, tol=0.1) # }) # # # # --------------------------- # context("BF lm") # x <- BayesFactor::lmBF(len ~ supp + dose, data = ToothGrowth) # test_that("p_direction", { # expect_equal(as.numeric(p_direction(x)), 91.9, tol=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)), 91.9, tol=0.1) # }) test_that("rope_range", { x <- BayesFactor::lmBF(len ~ supp + dose, data = ToothGrowth) expect_equal(rope_range(x)[2], sd(ToothGrowth$len) / 10) x <- BayesFactor::ttestBF( ToothGrowth$len[ToothGrowth$supp == "OJ"], ToothGrowth$len[ToothGrowth$supp == "VC"] ) expect_equal(rope_range(x)[2], sd(ToothGrowth$len) / 10) x <- BayesFactor::ttestBF(formula = len ~ supp, data = ToothGrowth) expect_equal(rope_range(x)[2], sd(ToothGrowth$len) / 10) # else x <- BayesFactor::correlationBF(ToothGrowth$len, ToothGrowth$dose) expect_equal(rope_range(x), c(-0.1, 0.1)) }) }