Nothing
test_that("Output of function 'sampleSizeSignificance' stays the same.", {
zo <- seq(-4, 4, 2)
grid <- expand.grid(
priors = c("conditional", "predictive", "EB"),
h = c(0, 0.1),
shrinkage = c(0, 0.75),
alt = c("one.sided", "two.sided"),
stringsAsFactors = FALSE
)
out <- lapply(
X = seq_len(nrow(grid)),
FUN = function(i) {
sampleSizeSignificance(
zo = zo,
power = 0.8,
level = 0.05,
designPrior = grid$priors[i],
alternative = grid$alt[i],
h = grid$h[i],
shrinkage = grid$shrinkage[i]
)
}
)
expect_equal(
out,
list(
c(0.386409827001236, 1.54563930800494, Inf, 1.54563930800494, 0.386409827001236),
c(0.440562894751761, 2.64240442300288, NA, 2.64240442300288, 0.440562894751761),
c(0.505683996618901, 5.68097835352188, NA, 5.68097835352188, 0.505683996618901),
c(0.386409827001236, 1.54563930800494, Inf, 1.54563930800494, 0.386409827001236),
c(0.452332524054221, 2.95871584108967, NA, 2.95871584108967, 0.452332524054221),
c(0.52827525176549, 7.60908343838383, NA, 7.60908343838383, 0.52827525176549),
c(6.18255723201977, 24.7302289280791, Inf, 24.7302289280791, 6.18255723201977),
c(113.100184785495, NA, NA, NA, 113.100184785495),
c(0.505683996618901, 5.68097835352188, NA, 5.68097835352188, 0.505683996618901),
c(6.18255723201977, 24.7302289280791, Inf, 24.7302289280791, 6.18255723201977),
c(453.912799705814, NA, NA, NA, 453.912799705814),
c(0.52827525176549, 7.60908343838383, NA, 7.60908343838383, 0.52827525176549),
c(0.490554983396818, 1.96221993358727, Inf, 1.96221993358727, 0.490554983396818),
c(0.567658970548963, 3.51088218947353, NA, 3.51088218947353, 0.567658970548963),
c(0.652140069510171, 7.6215454064467, NA, 7.6215454064467, 0.652140069510171),
c(0.490554983396818, 1.96221993358727, Inf, 1.96221993358727, 0.490554983396818),
c(0.584343691289888, 3.95487118399945, NA, 3.95487118399945, 0.584343691289888),
c(0.683282959536562, 10.3012684887906, NA, 10.3012684887906, 0.683282959536562),
c(7.84887973434909, 31.3955189373964, Inf, 31.3955189373964, 7.84887973434909),
c(158.405996395716, NA, NA, NA, 158.405996395716),
c(0.652140069510171, 7.6215454064467, NA, 7.6215454064467, 0.652140069510171),
c(7.84887973434909, 31.3955189373964, Inf, 31.3955189373964, 7.84887973434909),
c(640.395220372103, NA, NA, NA, 640.395220372103),
c(0.683282959536562, 10.3012684887906, NA, 10.3012684887906, 0.683282959536562)
)
)
})
test_that("numeric test for sampleSizeSignificance(): 1", {
za <- qnorm(p = 0.025, lower.tail = FALSE)
expect_equal(
object = sampleSizeSignificance(
zo = za, designPrior = "conditional",
power = 0.8, alternative = "one.sided"
),
expected = 2.04, tol = 0.01
)
})
test_that("sampleSizeSignificance() vs sampleSizeSignificanceNum", {
vec01bound <- c(0, 0.0386, 0.5031, 0.99)
vec55 <- c(-5, -2.6288, 0, 4)
alternative <- c("two.sided", "one.sided")
designPrior <- c("conditional", "predictive", "EB")
## power should only be larger than level
powvec <- c(0.499, 0.8, 0.975)
levelvec <- c(0.001, 0.025, 0.49)
pars_grid_power <- expand.grid(
zo = vec55,
power = powvec,
level = levelvec,
alternative = alternative,
designPrior = designPrior,
h = abs(vec55),
shrinkage = vec01bound,
stringsAsFactors = FALSE
)
## test all configurations separately
pars_grid <- cbind(pars_grid_power, new = NA, legacy = NA)
sampleSizeSignificanceNum <- ReplicationSuccess:::sampleSizeSignificanceNum
for (i in seq_len(nrow(pars_grid))) {
pars_grid[i, 9] <- do.call("sampleSizeSignificance", args = pars_grid[i, 1:7])
pars_grid[i, 10] <- do.call("sampleSizeSignificanceNum", args = pars_grid[i, 1:7])
}
## exclude cases with large values
pars_grid <- pars_grid[pars_grid$new < 1000, ]
expect_equal(object = is.na(pars_grid[, 9]), expected=is.na(pars_grid[, 10]))
pars_grid_nonNA <- pars_grid[!is.na(pars_grid[, 9]) & !is.na(pars_grid[, 10]), ]
expect_equal(object = pars_grid_nonNA[, 9], expected = pars_grid_nonNA[, 10], tol = 0.1)
})
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