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skip_on_os("linux")
test_that("model_parameters.BFBayesFactor", {
skip_on_cran()
skip("TODO")
skip_if_not_installed("BayesFactor")
model <- BayesFactor::ttestBF(iris$Sepal.Width, iris$Petal.Length, paired = TRUE)
expect_equal(model_parameters(model)$BF, c(492.770567186302, NA), tolerance = 1e-2)
})
# make sure BF is returned, even if NA
# see https://github.com/easystats/correlation/issues/269
test_that("model_parameters.BFBayesFactor", {
skip_if_not_installed("BayesFactor")
var_x <- c(
12.1, 8.7, 10.1, 17.4, 12.5, 2.7, 6.2, 19.4, 11, 14.5, 15.8,
10.4, 13.5, 3.5, 5.6, 5.2, 6.3, 12.5, 9.8
)
var_y <- c(
11.9, 15.3, 13.9, 6.6, 11.5, 21.35, 17.8, 4.6, 13, 9.5, 8.2,
13.6, 10.5, 20.5, 18.45, 18.8, 17.7, 11.5, 14.2
)
expect_warning({
model <- BayesFactor::correlationBF(var_x, var_y, rscale = "medium")
})
params <- model_parameters(model)
expect_identical(
colnames(params),
c(
"Parameter", "Median", "CI", "CI_low", "CI_high", "pd", "Prior_Distribution",
"Prior_Location", "Prior_Scale", "BF", "Method"
)
)
expect_true(is.na(params$BF))
})
test_that("model_parameters.BFBayesFactor", {
skip_if_not_installed("BayesFactor")
model <- BayesFactor::correlationBF(iris$Sepal.Width, iris$Petal.Length)
expect_equal(model_parameters(model)$BF, 348853.6, tolerance = 10)
})
test_that("model_parameters.BFBayesFactor", {
skip_if_not_installed("BayesFactor")
set.seed(123)
model <- BayesFactor::anovaBF(Sepal.Length ~ Species, data = iris, progress = FALSE)
expect_equal(
model_parameters(model, centrality = "median")$Median,
c(5.8431, -0.8266, 0.092, 0.734, 0.2681, 2.0415),
tolerance = 2
)
})
# test_that("model_parameters.BFBayesFactor", {
# skip_on_cran()
# model <- BayesFactor::ttestBF(formula = mpg ~ am, data = df)
# expect_equal(model_parameters(model)$BF, c(86.58973, NA), tolerance = 1)
# })
test_that("model_parameters.BFBayesFactor", {
skip_if_not_installed("BayesFactor")
df <- mtcars
df$gear <- as.factor(df$gear)
df$am <- as.factor(df$am)
set.seed(123)
model <- suppressMessages(BayesFactor::anovaBF(mpg ~ gear * am, data = df, progress = FALSE))
expect_equal(
suppressMessages(model_parameters(model, centrality = "mean", verbose = FALSE))$Mean,
c(20.7099, -3.24884, 3.24884, 26.51413, 5.30506, NA, NA, NA),
tolerance = 1L
)
})
test_that("model_parameters.BFBayesFactor", {
skip_on_cran()
skip_if_not_installed("BayesFactor")
data(raceDolls, package = "BayesFactor")
bf <- BayesFactor::contingencyTableBF(raceDolls, sampleType = "indepMulti", fixedMargin = "cols")
mp <- suppressWarnings(model_parameters(bf,
centrality = "mean",
dispersion = TRUE,
verbose = FALSE,
es_type = "cramers_v",
adjust = TRUE,
include_proportions = TRUE
))
mp2 <- suppressWarnings(model_parameters(bf, verbose = FALSE))
expect_identical(
colnames(mp),
c(
"Parameter", "Mean", "CI", "CI_low", "CI_high", "SD", "Cramers_v_adjusted",
"pd", "Prior_Distribution", "Prior_Location",
"Prior_Scale", "BF", "Method"
)
)
expect_identical(dim(mp), c(6L, 13L))
expect_identical(
colnames(mp2),
c(
"Parameter", "Prior_Distribution", "Prior_Location", "Prior_Scale",
"BF", "Method", "CI"
)
)
expect_identical(dim(mp2), c(1L, 7L))
})
test_that("model_parameters.BFBayesFactor", {
skip_on_cran()
skip_if_not_installed("BayesFactor")
data(puzzles, package = "BayesFactor")
result <- BayesFactor::anovaBF(RT ~ shape * color + ID,
data = puzzles, whichRandom = "ID",
whichModels = "top", progress = FALSE
)
mp <- suppressMessages(model_parameters(
result,
centrality = "median",
dispersion = TRUE,
verbose = FALSE
))
expect_identical(colnames(mp), c(
"Parameter", "Median", "MAD", "CI", "CI_low", "CI_high", "pd",
"Prior_Distribution", "Prior_Location", "Prior_Scale", "Effects",
"Component", "BF", "Method"
))
expect_identical(mp$Effects, c(
"fixed", "fixed", "fixed", "fixed", "fixed", "random", "random",
"random", "random", "random", "random", "random", "random", "random",
"random", "random", "random", "fixed", "fixed", "fixed", "fixed"
))
})
# one-sample t-test
test_that("model_parameters.BFBayesFactor, without effectsize", {
skip_if_not_installed("BayesFactor")
set.seed(123)
df_t <- as.data.frame(parameters(BayesFactor::ttestBF(mtcars$wt, mu = 3)))
expect_identical(
colnames(df_t),
c(
"Parameter", "Median", "CI", "CI_low", "CI_high", "pd",
"Prior_Distribution", "Prior_Location", "Prior_Scale", "BF",
"Method"
)
)
expect_identical(dim(df_t), c(1L, 11L))
})
test_that("model_parameters.BFBayesFactor, with effectsize", {
skip_if_not_installed("BayesFactor")
set.seed(123)
df_t_es <- as.data.frame(
parameters(BayesFactor::ttestBF(mtcars$wt, mu = 3), es_type = "cohens_d")
)
# TODO: fix column order
expect_identical(
colnames(df_t_es),
c(
"Parameter", "Median", "CI", "CI_low", "CI_high", "Cohens_d",
"d_CI_low", "d_CI_high", "pd", "Prior_Distribution", "Prior_Location",
"Prior_Scale", "BF", "Method"
)
)
expect_identical(dim(df_t_es), c(1L, 14L))
})
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