tests/testthat/test-sampleSizeSignificance.R

In SamCH93/ReplicationSuccess: Design and Analysis of Replication Studies

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)
})