context("VHSM score tests")
library(metafor)
library(purrr)
library(dplyr)
dat <- r_SMD(studies = 100, mean_effect = 0.1, sd_effect = 0.1,
n_sim = n_beta(10, 50, na = 3, nb = 3),
p_thresholds = .025, p_RR = 0.5)
dat$X1 <- rnorm(100)
dat$X2 <- sample(LETTERS[1:4], size = 100, replace = TRUE)
test_types <-
list(
type = c("parametric","robust"),
info = c("expected","observed"),
steps = list(one = .025, two = c(.025, .500))
) %>%
cross()
test_types <- test_types[c(-3, -7)]
test_that("Score tests work for intercept only models.", {
meta_fit <- rma(g, sei = sda, data = dat, method = "ML")
score_tests <- map_dfr(test_types, .f = ~ VHSM_score_test(meta_fit, steps = .$steps, type = .$type, info = .$info))
expect_true(is.data.frame(score_tests))
})
test_that("Score tests work for meta-regression models.", {
meta_reg <- rma(g ~ X1 + X2, sei = sda, data = dat, method = "ML")
score_tests <- map_dfr(test_types, .f = ~ VHSM_score_test(meta_reg, steps = .$steps, type = .$type, info = .$info))
expect_true(is.data.frame(score_tests))
})
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