swh:1:snp:2c68a6c5a8af2f06ac2c0225927f25b54fd1f9d0
Tip revision: d73e4a2afcfbd6402c11716877e8f7466f309ef4 authored by Dominique Makowski on 22 October 2020, 13:40:02 UTC
version 0.7.5
version 0.7.5
Tip revision: d73e4a2
test-p_significance.R
if (require("rstanarm", quietly = TRUE)) {
test_that("p_significance", {
set.seed(333)
x <- bayestestR::distribution_normal(10000, 1, 1)
ps <- bayestestR::p_significance(x)
testthat::expect_equal(as.numeric(ps), 0.816, tolerance = 0.1)
testthat::expect_equal(nrow(p_significance(data.frame(replicate(4, rnorm(100))))), 4)
testthat::expect_is(ps, "p_significance")
testthat::expect_equal(tail(capture.output(print(ps)), 1), "ps [0.10] = 81.60%")
})
.runThisTest <- Sys.getenv("RunAllbayestestRTests") == "yes"
if (.runThisTest) {
if (require("insight")) {
m <- insight::download_model("stanreg_merMod_5")
p <- insight::get_parameters(m, effects = "all")
testthat::expect_equal(
p_significance(m, effects = "all")$ps[1],
0.99,
tolerance = 1e-2
)
}
}
}