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skip_if_not_installed("metaBMA")
data(towels, package = "metaBMA")
set.seed(1234)
m <- suppressWarnings(
metaBMA::meta_random(
logOR,
SE,
study,
data = towels,
ci = 0.95,
iter = 100,
logml_iter = 200
)
)
test_that("model_parameters.meta_random", {
params <- model_parameters(m)
expect_identical(
params$Parameter,
c(
"Goldstein, Cialdini, & Griskevicius (2008), Exp. 1", "Goldstein, Cialdini, & Griskevicius (2008), Exp. 2",
"Schultz, Khazian, & Zaleski (2008), Exp. 2", "Schultz, Khazian, & Zaleski (2008), Exp. 3",
"Mair & Bergin-Seers (2010), Exp. 1", "Bohner & Schluter (2014), Exp. 1",
"Bohner & Schluter (2014), Exp. 2", "Overall", "tau"
)
)
expect_equal(
params$Coefficient,
c(0.3806, 0.30494, 0.20554, 0.25084, 0.28768, -0.12154, -1.45792, 0.2004, 0.12107),
tolerance = 1e-3
)
expect_equal(
params$CI_low,
c(-0.00686, 0.03816, -0.16998, -0.0825, -1.32685, -0.60772, -2.94785, -0.02744, 0.02641),
tolerance = 1e-3
)
expect_identical(
colnames(params),
c(
"Parameter", "Coefficient", "SE", "CI", "CI_low", "CI_high", "Weight",
"BF", "Rhat", "ESS", "Component", "Prior_Distribution", "Prior_Location", "Prior_Scale", "Method"
)
)
})
set.seed(1234)
m2 <- metaBMA::meta_fixed(
logOR,
SE,
study,
data = towels,
ci = 0.95
)
test_that("model_parameters.meta_fixed", {
params <- model_parameters(m2)
expect_identical(params$Parameter, c(
"Goldstein, Cialdini, & Griskevicius (2008), Exp. 1", "Goldstein, Cialdini, & Griskevicius (2008), Exp. 2",
"Schultz, Khazian, & Zaleski (2008), Exp. 2", "Schultz, Khazian, & Zaleski (2008), Exp. 3",
"Mair & Bergin-Seers (2010), Exp. 1", "Bohner & Schluter (2014), Exp. 1",
"Bohner & Schluter (2014), Exp. 2", "Overall"
))
expect_equal(params$Coefficient,
c(0.3806, 0.30494, 0.20554, 0.25084, 0.28768, -0.12154, -1.45792, 0.22141),
tolerance = 1e-3
)
expect_equal(
params$CI_low,
c(-0.00686, 0.03816, -0.16998, -0.0825, -1.32685, -0.60772, -2.94785, 0.06839),
tolerance = 1e-3
)
expect_identical(
colnames(params),
c(
"Parameter", "Coefficient", "SE", "CI", "CI_low", "CI_high", "Weight",
"BF", "Rhat", "ESS", "Component", "Prior_Distribution", "Prior_Location", "Prior_Scale", "Method"
)
)
})
set.seed(1234)
m3 <- suppressWarnings(
metaBMA::meta_random(
logOR,
SE,
study,
data = towels,
ci = 0.99,
iter = 100,
logml_iter = 200
)
)
test_that("model_parameters.meta_random", {
params <- model_parameters(m3)
expect_identical(
params$Parameter,
c(
"Goldstein, Cialdini, & Griskevicius (2008), Exp. 1", "Goldstein, Cialdini, & Griskevicius (2008), Exp. 2",
"Schultz, Khazian, & Zaleski (2008), Exp. 2", "Schultz, Khazian, & Zaleski (2008), Exp. 3",
"Mair & Bergin-Seers (2010), Exp. 1", "Bohner & Schluter (2014), Exp. 1",
"Bohner & Schluter (2014), Exp. 2", "Overall", "tau"
)
)
expect_equal(
params$Coefficient,
c(0.3806, 0.30494, 0.20554, 0.25084, 0.28768, -0.12154, -1.45792, 0.2004, 0.12107),
tolerance = 1e-3
)
expect_equal(
params$CI_low,
c(-0.00686, 0.03816, -0.16998, -0.0825, -1.32685, -0.60772, -2.94785, -0.15494, 0.01993),
tolerance = 1e-3
)
expect_identical(
colnames(params),
c(
"Parameter", "Coefficient", "SE", "CI", "CI_low", "CI_high", "Weight",
"BF", "Rhat", "ESS", "Component", "Prior_Distribution", "Prior_Location", "Prior_Scale", "Method"
)
)
})
|
