Nothing
library(metaBMA)
library(testthat)
set.seed(123)
test_that("meta_sensitivity() expected results", {
expect_silent(sens <- meta_sensitivity(
logOR, SE, study, towels,
d_list = list(prior("cauchy", c(0, .707)),
prior("norm", c(.5, .3))),
tau_list = list(prior("invgamma", c(1, 0.15), label = "tau"),
prior("gamma", c(1.5, 3), label = "tau")),
analysis = "fixed", combine_priors = "matched"))
expect_length(sens, 2)
expect_type(sens, "list")
expect_output(print(sens))
expect_output(plot(sens))
expect_output(plot(sens, distribution = "prior", from = -2, to = 2, n = 31))
skip_on_cran()
suppressWarnings(sens <- meta_sensitivity(
logOR, SE, study, towels,
d_list = list(prior("cauchy", c(0, .707)),
prior("norm", c(.5, .3))),
tau_list = list(prior("cauchy", c(0,.5), lower = 0, label = "tau"),
prior("gamma", c(1.5, 3), label = "tau")),
analysis = "random", combine_priors = "matched"))
expect_length(sens, 2)
expect_type(sens, "list")
expect_output(print(sens))
skip_on_cran()
suppressWarnings(sens <- meta_sensitivity(
logOR, SE, study, towels,
d_list = list(prior("cauchy", c(0, .707)),
prior("norm", c(.5, .3))),
tau_list = list(prior("cauchy", c(0,.5), lower = 0, label = "tau"),
prior("gamma", c(1.1, 3), label = "tau")),
analysis = "bma", combine_priors = "crossed"))
expect_length(sens, 2*2)
expect_type(sens, "list")
expect_output(print(sens))
expect_output(plot(sens, parameter = "d"))
expect_output(plot(sens, distr = "prior", parameter = "d"))
expect_warning(plot(sens, parameter = "tau", legend = FALSE))
expect_warning(plot(sens, distr = "prior", parameter = "tau", legend = FALSE))
})
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