Nothing
tests/testthat/test-design-generators.R
In lrstat: Power and Sample Size Calculation for Non-Proportional Hazards and Beyond
testthat::test_that("getDesign: documented example returns stable design object", {
design1 <- getDesign(
beta = 0.2,
theta = -log(0.7),
kMax = 2,
informationRates = c(0.5, 1),
alpha = 0.025,
typeAlphaSpending = "sfOF",
typeBetaSpending = "sfP"
)
testthat::expect_s3_class(design1, "design")
testthat::expect_named(design1, c("byStageResults", "overallResults", "settings"))
# Printed summary reports power and max information; verify numerically.
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.8000)
testthat::expect_equal(round(design1$overallResults$information, 2), 71.97)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[1], 3), 2.963)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[2], 3), 1.969)
})
testthat::test_that("getDesign_multiarm: documented example returns stable multiarm object", {
design1 <- getDesign_multiarm(
beta = 0.1,
theta = c(0.3, 0.5),
M = 2,
r = 1.0,
kMax = 3,
informationRates = seq(1, 3) / 3,
alpha = 0.025,
typeAlphaSpending = "OF"
)
testthat::expect_s3_class(design1, "multiarm")
testthat::expect_named(design1,
c("byStageResults", "byLevelBounds", "overallResults", "settings"))
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9000)
testthat::expect_equal(round(design1$overallResults$information, 2), 47.15)
testthat::expect_equal(
round(design1$byStageResults$efficacyBounds, 3),
c(3.887, 2.748, 2.244)
)
})
testthat::test_that("getDesign_seamless: object contract and boundary dimensions", {
design1 <- getDesign_seamless(
beta = 0.1,
theta = c(0.3, 0.5),
M = 2,
r = 1.0,
K = 2,
informationRates = seq(1, 3) / 3,
alpha = 0.025,
typeAlphaSpending = "OF"
)
testthat::expect_s3_class(design1, "seamless")
testthat::expect_true("overallResults" %in% names(design1))
testthat::expect_true("byStageResults" %in% names(design1))
testthat::expect_true("settings" %in% names(design1))
testthat::expect_equal(nrow(design1$byStageResults), 3)
testthat::expect_true(all(design1$byStageResults$efficacyBounds > 0))
})
testthat::test_that("getDesign wrappers: invalid alpha is rejected", {
testthat::expect_error(
getDesign(beta = 0.2, theta = 0.4, kMax = 2, informationRates = c(0.5, 1), alpha = -0.1),
regexp = "alpha|significance"
)
testthat::expect_error(
getDesign_multiarm(beta = 0.1, theta = c(0.3, 0.5), M = 2, kMax = 3,
informationRates = seq(1, 3) / 3, alpha = -0.1),
regexp = "alpha|significance"
)
testthat::expect_error(
getDesign_seamless(beta = 0.1, theta = c(0.3, 0.5), M = 2, K = 2,
informationRates = seq(1, 3) / 3, alpha = -0.1),
regexp = "alpha|significance"
)
})
testthat::test_that("getDesignRiskDiff: Rd example numeric regression", {
design1 <- getDesignRiskDiff(
beta = 0.2,
n = NA,
pi1 = 0.1,
pi2 = 0.15,
kMax = 3,
alpha = 0.025,
typeAlphaSpending = "sfOF",
nullVariance = FALSE
)
testthat::expect_s3_class(design1, "designRiskDiff")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.8002)
testthat::expect_equal(round(design1$overallResults$numberOfSubjects, 0), 1384)
testthat::expect_equal(
round(design1$byStageResults$efficacyBounds, 3),
c(3.712, 2.511, 1.993)
)
})
testthat::test_that("getDesignOneProportion: Rd examples numeric regression", {
design1 <- getDesignOneProportion(
beta = 0.2,
n = NA,
piH0 = 0.15,
pi = 0.25,
kMax = 3,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
design2 <- getDesignOneProportion(
beta = 0.2,
n = NA,
piH0 = 0.15,
pi = 0.25,
normalApproximation = FALSE,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designOneProportion")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.8012)
testthat::expect_equal(round(design1$overallResults$numberOfSubjects, 0), 91)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[3], 3), 1.696)
testthat::expect_s3_class(design2, "designOneProportion")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.8097)
testthat::expect_equal(round(design2$overallResults$numberOfSubjects, 0), 110)
})
testthat::test_that("getDesignFisherExact: Rd example numeric regression", {
design1 <- getDesignFisherExact(
beta = 0.2,
pi1 = 0.5,
pi2 = 0.2,
alpha = 0.05
)
testthat::expect_s3_class(design1, "data.frame")
testthat::expect_equal(round(design1$power, 4), 0.8168)
testthat::expect_equal(design1$n, 87)
})
testthat::test_that("getDesignMeanDiff: Rd examples numeric regression", {
design1 <- getDesignMeanDiff(
beta = NA,
n = 456,
meanDiff = 9,
stDev = 32,
kMax = 5,
alpha = 0.025,
typeAlphaSpending = "sfOF",
typeBetaSpending = "sfP"
)
design2 <- getDesignMeanDiff(
beta = 0.1,
n = NA,
meanDiff = 0.3,
stDev = 1,
normalApproximation = FALSE,
alpha = 0.025
)
testthat::expect_s3_class(design1, "designMeanDiff")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.7421)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 456)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[1], 3), 4.883)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[5], 3), 2.031)
testthat::expect_s3_class(design2, "designMeanDiff")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9000)
testthat::expect_equal(round(design2$overallResults$numberOfSubjects, 0), 469)
})
testthat::test_that("getDesignWilcoxon: Rd examples numeric regression", {
p_larger <- pnorm((8 - 2) / sqrt(2 * 25^2))
design1 <- getDesignWilcoxon(
beta = 0.1,
n = NA,
pLarger = p_larger,
alpha = 0.025
)
design2 <- getDesignWilcoxon(
beta = 0.1,
n = NA,
pLarger = p_larger,
alpha = 0.025,
kMax = 3,
typeAlphaSpending = "sfOF"
)
testthat::expect_s3_class(design1, "designWilcoxon")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9002)
testthat::expect_equal(round(design1$overallResults$numberOfSubjects, 0), 772)
testthat::expect_s3_class(design2, "designWilcoxon")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9001)
testthat::expect_equal(round(design2$overallResults$numberOfSubjects, 0), 781)
testthat::expect_equal(
round(design2$byStageResults$efficacyBounds, 3),
c(3.713, 2.510, 1.993)
)
})
testthat::test_that("getDesignOddsRatio: Rd example numeric regression", {
design1 <- getDesignOddsRatio(
beta = 0.1,
n = NA,
pi1 = 0.5,
pi2 = 0.3,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designOddsRatio")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9012)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 210)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[1], 3), 1.645)
})
testthat::test_that("getDesignRiskRatio: Rd example numeric regression", {
design1 <- getDesignRiskRatio(
beta = 0.1,
n = NA,
pi1 = 0.5,
pi2 = 0.3,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designRiskRatio")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9008)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 207)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[1], 3), 1.645)
})
testthat::test_that("getDesignOneMean: Rd examples numeric regression", {
design1 <- getDesignOneMean(
beta = 0.1,
n = NA,
meanH0 = 7,
mean = 6,
stDev = 2.5,
kMax = 5,
alpha = 0.025,
typeAlphaSpending = "sfOF",
typeBetaSpending = "sfP"
)
design2 <- getDesignOneMean(
beta = 0.1,
n = NA,
meanH0 = 7,
mean = 6,
stDev = 2.5,
normalApproximation = FALSE,
alpha = 0.025
)
testthat::expect_s3_class(design1, "designOneMean")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9016)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 85)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[1], 3), 4.877)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[5], 3), 2.031)
testthat::expect_s3_class(design2, "designOneMean")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9016)
testthat::expect_equal(design2$overallResults$numberOfSubjects, 68)
testthat::expect_equal(round(design2$byStageResults$efficacyBounds[1], 3), 1.996)
})
testthat::test_that("getDesignANOVA: Rd example numeric regression", {
design1 <- getDesignANOVA(
beta = 0.1,
ngroups = 4,
means = c(1.5, 2.5, 2, 0),
stDev = 3.5,
allocationRatioPlanned = c(2, 2, 2, 1),
alpha = 0.05
)
testthat::expect_s3_class(design1, "designANOVA")
testthat::expect_equal(round(design1$power, 4), 0.9008)
testthat::expect_equal(design1$n, 279)
testthat::expect_equal(round(design1$effectsize, 4), 0.0516)
})
testthat::test_that("getDesignTwoOrdinal: Rd example numeric regression", {
design1 <- getDesignTwoOrdinal(
beta = 0.1,
ncats = 4,
pi1 = c(0.55, 0.3, 0.1),
pi2 = c(0.214, 0.344, 0.251),
alpha = 0.025
)
testthat::expect_s3_class(design1, "designTwoOrdinal")
testthat::expect_equal(round(design1$power, 4), 0.9030)
testthat::expect_equal(design1$n, 67)
testthat::expect_equal(round(design1$meanscore1, 4), 26.4055)
testthat::expect_equal(round(design1$meanscore2, 4), 40.5945)
})
testthat::test_that("getDesignOddsRatioEquiv: Rd example numeric regression", {
design1 <- getDesignOddsRatioEquiv(
beta = 0.2,
n = NA,
oddsRatioLower = 0.8,
oddsRatioUpper = 1.25,
pi1 = 0.12,
pi2 = 0.12,
kMax = 3,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
testthat::expect_s3_class(design1, "designOddsRatioEquiv")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.8000)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 6637)
testthat::expect_equal(round(design1$overallResults$information, 4), 175.2168)
testthat::expect_equal(
round(design1$byStageResults$efficacyBounds, 3),
c(3.200, 2.141, 1.695)
)
})
testthat::test_that("getDesignRiskRatioEquiv: Rd example numeric regression", {
design1 <- getDesignRiskRatioEquiv(
beta = 0.2,
n = NA,
riskRatioLower = 0.8,
riskRatioUpper = 1.25,
pi1 = 0.12,
pi2 = 0.12,
kMax = 3,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
testthat::expect_s3_class(design1, "designRiskRatioEquiv")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.8000)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 5140)
testthat::expect_equal(round(design1$overallResults$information, 4), 175.2273)
testthat::expect_equal(
round(design1$byStageResults$efficacyBounds, 3),
c(3.200, 2.141, 1.695)
)
})
testthat::test_that("getDesignOneRateExact: Rd examples numeric regression", {
design1 <- getDesignOneRateExact(
n = 525,
lambdaH0 = 0.049,
lambda = 0.012,
D = 0.5,
alpha = 0.025
)
design2 <- getDesignOneRateExact(
beta = 0.2,
lambdaH0 = 0.2,
lambda = 0.3,
D = 1,
alpha = 0.05
)
testthat::expect_s3_class(design1, "data.frame")
testthat::expect_equal(round(design1$power, 4), 0.9002)
testthat::expect_equal(round(design1$attainedAlpha, 4), 0.0117)
testthat::expect_equal(design1$n, 525)
testthat::expect_equal(design1$r, 5)
testthat::expect_s3_class(design2, "data.frame")
testthat::expect_equal(round(design2$power, 4), 0.8078)
testthat::expect_equal(round(design2$attainedAlpha, 4), 0.0427)
testthat::expect_equal(design2$n, 162)
testthat::expect_equal(design2$r, 43)
})
testthat::test_that("getDesignANOVAContrast: Rd example numeric regression", {
design1 <- getDesignANOVAContrast(
beta = 0.1,
ngroups = 4,
means = c(1.5, 2.5, 2, 0),
stDev = 3.5,
contrast = c(1, 1, 1, -3),
allocationRatioPlanned = c(2, 2, 2, 1),
alpha = 0.025
)
testthat::expect_s3_class(design1, "designANOVAContrast")
testthat::expect_equal(round(design1$power, 4), 0.9003)
testthat::expect_equal(design1$n, 265)
testthat::expect_equal(round(design1$effectsize, 4), 0.0400)
testthat::expect_equal(design1$meanContrast, 6)
})
testthat::test_that("getDesignRepeatedANOVA: Rd example numeric regression", {
design1 <- getDesignRepeatedANOVA(
beta = 0.1,
ngroups = 4,
means = c(1.5, 2.5, 2, 0),
stDev = 5,
corr = 0.2,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designRepeatedANOVA")
testthat::expect_equal(round(design1$power, 4), 0.9027)
testthat::expect_equal(design1$n, 83)
testthat::expect_equal(round(design1$effectsize, 3), 0.175)
})
testthat::test_that("getDesignMeanDiffEquiv: Rd examples numeric regression", {
design1 <- getDesignMeanDiffEquiv(
beta = 0.1,
n = NA,
meanDiffLower = -1.3,
meanDiffUpper = 1.3,
meanDiff = 0,
stDev = 2.2,
kMax = 4,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
design2 <- getDesignMeanDiffEquiv(
beta = 0.1,
n = NA,
meanDiffLower = -1.3,
meanDiffUpper = 1.3,
meanDiff = 0,
stDev = 2.2,
normalApproximation = FALSE,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designMeanDiffEquiv")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9024)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 128)
testthat::expect_equal(round(design1$overallResults$information, 4), 6.6116)
testthat::expect_equal(
round(design1$byStageResults$efficacyBounds, 3),
c(3.750, 2.540, 2.016, 1.720)
)
testthat::expect_s3_class(design2, "designMeanDiffEquiv")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9018)
testthat::expect_equal(design2$overallResults$numberOfSubjects, 126)
testthat::expect_equal(round(design2$byStageResults$efficacyBounds[1], 3), 1.657)
})
testthat::test_that("getDesignAgreement: Rd example numeric regression", {
design1 <- getDesignAgreement(
beta = 0.2,
n = NA,
ncats = 4,
kappaH0 = 0.4,
kappa = 0.6,
p1 = c(0.1, 0.2, 0.3, 0.4),
p2 = c(0.15, 0.2, 0.24, 0.41),
rounding = TRUE,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designAgreement")
testthat::expect_equal(round(design1$power, 4), 0.8006)
testthat::expect_equal(design1$n, 82)
})
testthat::test_that("getDesignEquiv: Rd example numeric regression", {
design1 <- getDesignEquiv(
beta = 0.2,
thetaLower = log(0.8),
thetaUpper = log(1.25),
kMax = 2,
informationRates = c(0.5, 1),
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
testthat::expect_s3_class(design1, "designEquiv")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.8000)
testthat::expect_equal(round(design1$overallResults$information, 4), 173.2257)
})
testthat::test_that("getDesignLogistic: Rd example numeric regression", {
x1 <- c(5, 10, 15, 20)
px1 <- c(0.2, 0.3, 0.3, 0.2)
x2 <- c(2, 4, 6)
px2 <- c(0.4, 0.4, 0.2)
nbins <- 10
x3 <- qnorm(((1:nbins) - 0.5) / nbins) * 2 + 4
px3 <- rep(1 / nbins, nbins)
nconfigs <- length(x1) * length(x2) * length(x3)
x <- expand.grid(x3 = x3, x2 = x2, x1 = x1)
x <- as.matrix(x[, ncol(x):1])
pconfigs <- as.numeric(px1 %x% px2 %x% px3)
design1 <- getDesignLogistic(
beta = 0.1,
ncovariates = 3,
nconfigs = nconfigs,
x = x,
pconfigs = pconfigs,
oddsratios = c(1.2^(1/5), 1.4, 1.3),
responseprob = 0.25,
alpha = 0.1
)
testthat::expect_s3_class(design1, "designLogistic")
testthat::expect_equal(round(design1$power, 4), 0.9002)
testthat::expect_equal(design1$n, 1369)
testthat::expect_equal(round(design1$effectsize, 4), 0.0063)
})
testthat::test_that("getDesignMeanRatio: Rd example numeric regression", {
design1 <- getDesignMeanRatio(
beta = 0.1,
n = NA,
meanRatio = 1.25,
CV = 0.35,
kMax = 3,
alpha = 0.025,
typeAlphaSpending = "sfOF"
)
testthat::expect_s3_class(design1, "designMeanRatio")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9009)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 99)
})
testthat::test_that("getDesignOneMultinom: Rd example numeric regression", {
design1 <- getDesignOneMultinom(
beta = 0.1,
ncats = 3,
piH0 = c(0.25, 0.25),
pi = c(0.3, 0.4),
alpha = 0.05
)
testthat::expect_s3_class(design1, "designOneMultinom")
testthat::expect_equal(round(design1$power, 4), 0.9030)
testthat::expect_equal(design1$n, 71)
})
testthat::test_that("getDesignMeanRatioEquiv: Rd examples numeric regression", {
design1 <- getDesignMeanRatioEquiv(
beta = 0.1,
n = NA,
meanRatioLower = 0.8,
meanRatioUpper = 1.25,
meanRatio = 1,
CV = 0.35,
kMax = 4,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
design2 <- getDesignMeanRatioEquiv(
beta = 0.1,
n = NA,
meanRatioLower = 0.8,
meanRatioUpper = 1.25,
meanRatio = 1,
CV = 0.35,
normalApproximation = FALSE,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designMeanRatioEquiv")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9033)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 104)
testthat::expect_equal(round(design1$overallResults$information, 4), 224.9946)
testthat::expect_equal(
round(design1$byStageResults$efficacyBounds, 3),
c(3.750, 2.540, 2.016, 1.720)
)
testthat::expect_s3_class(design2, "designMeanRatioEquiv")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9005)
testthat::expect_equal(design2$overallResults$numberOfSubjects, 102)
testthat::expect_equal(round(design2$byStageResults$efficacyBounds[1], 3), 1.660)
})
testthat::test_that("getDesignRiskDiffEquiv: Rd example numeric regression", {
design1 <- getDesignRiskDiffEquiv(
beta = 0.2,
n = NA,
riskDiffLower = -0.1,
riskDiffUpper = 0.1,
pi1 = 0.12,
pi2 = 0.12,
kMax = 3,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
testthat::expect_s3_class(design1, "designRiskDiffEquiv")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.8007)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 369)
testthat::expect_equal(round(design1$overallResults$information, 4), 873.5795)
testthat::expect_equal(
round(design1$byStageResults$efficacyBounds, 3),
c(3.200, 2.141, 1.695)
)
})
testthat::test_that("getDesignRepeatedANOVAContrast: Rd example numeric regression", {
design1 <- getDesignRepeatedANOVAContrast(
beta = 0.1,
ngroups = 4,
means = c(1.5, 2.5, 2, 0),
stDev = 5,
corr = 0.2,
contrast = c(1, 1, 1, -3) / 3,
alpha = 0.025
)
testthat::expect_s3_class(design1, "designRepeatedANOVAContrast")
testthat::expect_equal(round(design1$power, 4), 0.9012)
testthat::expect_equal(design1$n, 71)
testthat::expect_equal(round(design1$effectsize, 3), 0.150)
testthat::expect_equal(design1$meanContrast, 2)
})
testthat::test_that("getDesignMeanDiffCarryover: Rd example numeric regression", {
design1 <- getDesignMeanDiffCarryover(
beta = 0.2,
n = NA,
meanDiff = 0.5,
stDev = 1,
design = matrix(c(1, 4, 2, 3,
2, 1, 3, 4,
3, 2, 4, 1,
4, 3, 1, 2),
4, 4, byrow = TRUE),
alpha = 0.025
)
testthat::expect_s3_class(design1, "designMeanDiffCarryover")
testthat::expect_equal(round(design1$power, 4), 0.8015)
testthat::expect_equal(design1$numberOfSubjects, 70)
})
testthat::test_that("getDesignMeanDiffCarryoverEquiv: Rd example numeric regression", {
design1 <- getDesignMeanDiffCarryoverEquiv(
beta = 0.2,
n = NA,
meanDiffLower = -1.3,
meanDiffUpper = 1.3,
meanDiff = 0,
stDev = 2.2,
design = matrix(c(1, 4, 2, 3,
2, 1, 3, 4,
3, 2, 4, 1,
4, 3, 1, 2),
4, 4, byrow = TRUE),
alpha = 0.025
)
testthat::expect_s3_class(design1, "designMeanDiffCarryoverEquiv")
testthat::expect_equal(round(design1$power, 4), 0.8011)
testthat::expect_equal(design1$numberOfSubjects, 67)
})
testthat::test_that("getDesignMeanDiffXOEquiv: Rd examples numeric regression", {
design1 <- getDesignMeanDiffXOEquiv(
beta = 0.1,
n = NA,
meanDiffLower = -1.3,
meanDiffUpper = 1.3,
meanDiff = 0,
stDev = 2.2,
kMax = 4,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
design2 <- getDesignMeanDiffXOEquiv(
beta = 0.1,
n = NA,
meanDiffLower = -1.3,
meanDiffUpper = 1.3,
meanDiff = 0,
stDev = 2.2,
normalApproximation = FALSE,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designMeanDiffXOEquiv")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9024)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 64)
testthat::expect_s3_class(design2, "designMeanDiffXOEquiv")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9033)
testthat::expect_equal(design2$overallResults$numberOfSubjects, 64)
})
testthat::test_that("getDesignMeanDiffXO: Rd example numeric regression", {
design1 <- getDesignMeanDiffXO(
beta = 0.2,
n = NA,
meanDiff = 75,
stDev = 150,
normalApproximation = FALSE,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designMeanDiffXO")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.8009)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 51)
})
testthat::test_that("getDesignMeanRatioXO: Rd example numeric regression", {
design1 <- getDesignMeanRatioXO(
beta = 0.1,
n = NA,
meanRatio = 1.25,
CV = 0.25,
alpha = 0.05,
normalApproximation = FALSE
)
testthat::expect_s3_class(design1, "designMeanRatioXO")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9078)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 23)
})
testthat::test_that("getDesignMeanRatioXOEquiv: Rd examples numeric regression", {
design1 <- getDesignMeanRatioXOEquiv(
beta = 0.1,
n = NA,
meanRatioLower = 0.8,
meanRatioUpper = 1.25,
meanRatio = 1,
CV = 0.35,
kMax = 4,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
design2 <- getDesignMeanRatioXOEquiv(
beta = 0.1,
n = NA,
meanRatioLower = 0.8,
meanRatioUpper = 1.25,
meanRatio = 1,
CV = 0.35,
normalApproximation = FALSE,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designMeanRatioXOEquiv")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9033)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 52)
testthat::expect_s3_class(design2, "designMeanRatioXOEquiv")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9024)
testthat::expect_equal(design2$overallResults$numberOfSubjects, 52)
})
testthat::test_that("getDesignOrderedBinom: Rd example numeric regression", {
design1 <- getDesignOrderedBinom(
beta = 0.1,
ngroups = 3,
pi = c(0.1, 0.25, 0.5),
alpha = 0.05
)
testthat::expect_s3_class(design1, "designOrderedBinom")
testthat::expect_equal(round(design1$power, 4), 0.9011)
testthat::expect_equal(design1$n, 75)
})
testthat::test_that("getDesignPairedMeanDiff: Rd examples numeric regression", {
design1 <- getDesignPairedMeanDiff(
beta = 0.1,
n = NA,
pairedDiffH0 = 0,
pairedDiff = -2,
stDev = 5,
kMax = 5,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
design2 <- getDesignPairedMeanDiff(
beta = 0.1,
n = NA,
pairedDiffH0 = 0,
pairedDiff = -2,
stDev = 5,
normalApproximation = FALSE,
alpha = 0.025
)
testthat::expect_s3_class(design1, "designPairedMeanDiff")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9033)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 56)
testthat::expect_s3_class(design2, "designPairedMeanDiff")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9016)
testthat::expect_equal(design2$overallResults$numberOfSubjects, 68)
})
testthat::test_that("getDesignPairedMeanDiffEquiv: Rd examples numeric regression", {
design1 <- getDesignPairedMeanDiffEquiv(
beta = 0.1,
n = NA,
pairedDiffLower = -1.3,
pairedDiffUpper = 1.3,
pairedDiff = 0,
stDev = 2.2,
kMax = 4,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
design2 <- getDesignPairedMeanDiffEquiv(
beta = 0.1,
n = NA,
pairedDiffLower = -1.3,
pairedDiffUpper = 1.3,
pairedDiff = 0,
stDev = 2.2,
normalApproximation = FALSE,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designPairedMeanDiffEquiv")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9024)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 32)
testthat::expect_s3_class(design2, "designPairedMeanDiffEquiv")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9064)
testthat::expect_equal(design2$overallResults$numberOfSubjects, 33)
})
testthat::test_that("getDesignMeanDiffMMRM: Rd example numeric regression", {
design1 <- getDesignMeanDiffMMRM(
beta = 0.1,
meanDiff = 0.5,
k = 2,
t = c(1, 2),
accrualIntensity = 40,
accrualDuration = 1
)
testthat::expect_s3_class(design1, "designMeanDiffMMRM")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9015)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 169)
})
testthat::test_that("getDesignOneSlope: Rd example numeric regression", {
design1 <- getDesignOneSlope(
beta = 0.1,
n = NA,
slope = 1,
stDev = 1,
stDevCovariate = 1,
alpha = 0.025
)
testthat::expect_s3_class(design1, "designOneSlope")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9126)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 11)
})
testthat::test_that("getDesignPairedMeanRatio: Rd example numeric regression", {
design1 <- getDesignPairedMeanRatio(
beta = 0.1,
n = NA,
pairedRatio = 1.2,
CV = 0.35,
alpha = 0.05,
normalApproximation = FALSE
)
testthat::expect_s3_class(design1, "designPairedMeanRatio")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9069)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 32)
})
testthat::test_that("getDesignPairedMeanRatioEquiv: Rd examples numeric regression", {
design1 <- getDesignPairedMeanRatioEquiv(
beta = 0.1,
n = NA,
pairedRatioLower = 0.8,
pairedRatioUpper = 1.25,
pairedRatio = 1,
CV = 0.35,
kMax = 4,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
design2 <- getDesignPairedMeanRatioEquiv(
beta = 0.1,
n = NA,
pairedRatioLower = 0.8,
pairedRatioUpper = 1.25,
pairedRatio = 1,
CV = 0.35,
normalApproximation = FALSE,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designPairedMeanRatioEquiv")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9029)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 26)
testthat::expect_s3_class(design2, "designPairedMeanRatioEquiv")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9061)
testthat::expect_equal(design2$overallResults$numberOfSubjects, 27)
})
testthat::test_that("getDesignRiskDiffExact: Rd example numeric regression", {
design1 <- getDesignRiskDiffExact(
n = 50,
pi1 = 0.6,
pi2 = 0.25,
alpha = 0.025
)
testthat::expect_s3_class(design1, "data.frame")
testthat::expect_equal(design1$power, 0.694611217040014)
testthat::expect_equal(design1$n, 50)
})
testthat::test_that("getDesignRiskDiffExactEquiv: Rd example numeric regression", {
design1 <- getDesignRiskDiffExactEquiv(
n = 200,
riskDiffLower = -0.2,
riskDiffUpper = 0.2,
pi1 = 0.775,
pi2 = 0.775,
alpha = 0.05
)
testthat::expect_s3_class(design1, "data.frame")
testthat::expect_equal(round(design1$power, 4), 0.9147)
testthat::expect_equal(design1$n, 200)
})
testthat::test_that("getDesignRiskRatioExact: Rd example numeric regression", {
design1 <- getDesignRiskRatioExact(
beta = 0.2,
riskRatioH0 = 0.7,
pi1 = 0.95,
pi2 = 0.95,
alpha = 0.025
)
testthat::expect_s3_class(design1, "data.frame")
testthat::expect_equal(round(design1$power, 4), 0.8573)
testthat::expect_equal(design1$n, 39)
})
testthat::test_that("getDesignRiskRatioExactEquiv: Rd example numeric regression", {
design1 <- getDesignRiskRatioExactEquiv(
n = 200,
riskRatioLower = 0.8,
riskRatioUpper = 1.25,
pi1 = 0.775,
pi2 = 0.775,
alpha = 0.05
)
testthat::expect_s3_class(design1, "data.frame")
testthat::expect_equal(round(design1$power, 4), 0.7514)
testthat::expect_equal(design1$n, 200)
})
testthat::test_that("getDesignRiskRatioFM: Rd example numeric regression", {
design1 <- getDesignRiskRatioFM(
beta = 0.2,
riskRatioH0 = 1.3,
pi1 = 0.125,
pi2 = 0.125,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designRiskRatioFM")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.8001)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 2531)
})
testthat::test_that("getDesignPairedPropMcNemar: Rd examples numeric regression", {
design1 <- getDesignPairedPropMcNemar(
beta = 0.1,
n = NA,
pDiscordant = 0.16,
riskDiff = 0.1,
alpha = 0.025
)
design2 <- getDesignPairedPropMcNemar(
beta = 0.1,
n = NA,
pDiscordant = 0.16,
riskDiff = 0.1,
alpha = 0.025,
kMax = 3,
typeAlphaSpending = "sfOF"
)
testthat::expect_s3_class(design1, "designPairedPropMcNemar")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9001)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 164)
testthat::expect_s3_class(design2, "designPairedPropMcNemar")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9016)
testthat::expect_equal(design2$overallResults$numberOfSubjects, 167)
testthat::expect_equal(
round(design2$byStageResults$efficacyBounds, 3),
c(3.698, 2.516, 1.993)
)
})
testthat::test_that("getDesignSlopeDiff: Rd example numeric regression", {
design1 <- getDesignSlopeDiff(
beta = 0.1,
n = NA,
slopeDiff = -0.5,
stDev = 10,
stDevCovariate = 6,
normalApproximation = FALSE,
alpha = 0.025
)
testthat::expect_s3_class(design1, "designSlopeDiff")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9000)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 469)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[1], 3), 1.965)
})
testthat::test_that("getDesignSlopeDiffMMRM: Rd example numeric regression", {
design1 <- getDesignSlopeDiffMMRM(
beta = 0.2,
slopeDiff = log(1.15) / 52,
stDev = sqrt(.182),
stDevIntercept = sqrt(.238960),
stDevSlope = sqrt(.000057),
corrInterceptSlope = .003688 / sqrt(.238960 * .000057),
w = 8,
N = 10000,
accrualIntensity = 15,
gamma1 = 1 / (4.48 * 52),
gamma2 = 1 / (4.48 * 52),
accrualDuration = NA,
followupTime = 8,
alpha = 0.025
)
testthat::expect_s3_class(design1, "designSlopeDiffMMRM")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.8004)
testthat::expect_equal(round(design1$overallResults$information, 0), 1087517)
testthat::expect_equal(round(design1$overallResults$numberOfSubjects, 0), 1013)
testthat::expect_equal(round(design1$overallResults$studyDuration, 4), 75.5333)
testthat::expect_equal(round(design1$overallResults$accrualDuration, 4), 67.5333)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[1], 3), 1.960)
})
testthat::test_that("getDesignTwoMultinom: Rd example numeric regression", {
design1 <- getDesignTwoMultinom(
beta = 0.1,
ncats = 3,
pi1 = c(0.3, 0.35),
pi2 = c(0.2, 0.3),
alpha = 0.05
)
testthat::expect_s3_class(design1, "designTwoMultinom")
testthat::expect_equal(round(design1$power, 4), 0.9000)
testthat::expect_equal(design1$n, 503)
testthat::expect_equal(round(design1$effectsize, 4), 0.0252)
})
testthat::test_that("getDesignTwoWayANOVA: Rd example numeric regression", {
design1 <- getDesignTwoWayANOVA(
beta = 0.1,
nlevelsA = 2,
nlevelsB = 2,
means = matrix(c(0.5, 4.7, 0.4, 6.9), 2, 2, byrow = TRUE),
stDev = 2,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designTwoWayANOVA")
testthat::expect_equal(design1$powerdf$n[1], 156)
testthat::expect_equal(round(design1$powerdf$powerA[1], 4), 0.9028)
testthat::expect_equal(round(design1$powerdf$powerB[1], 4), 1.0000)
testthat::expect_equal(round(design1$powerdf$powerAB[1], 4), 0.9461)
testthat::expect_equal(round(design1$effectsizeAB, 4), 0.0827)
})
testthat::test_that("getDesignUnorderedBinom: Rd example numeric regression", {
design1 <- getDesignUnorderedBinom(
beta = 0.1,
ngroups = 3,
pi = c(0.1, 0.25, 0.5),
alpha = 0.05
)
testthat::expect_s3_class(design1, "designUnorderedBinom")
testthat::expect_equal(round(design1$power, 4), 0.9020)
testthat::expect_equal(design1$n, 95)
testthat::expect_equal(round(design1$effectsize, 4), 0.1341)
})
testthat::test_that("getDesignUnorderedMultinom: Rd example numeric regression", {
design1 <- getDesignUnorderedMultinom(
beta = 0.1,
ngroups = 3,
ncats = 4,
pi = matrix(c(0.230, 0.320, 0.272,
0.358, 0.442, 0.154,
0.142, 0.036, 0.039),
3, 3, byrow = TRUE),
allocationRatioPlanned = c(2, 2, 1),
alpha = 0.05
)
testthat::expect_s3_class(design1, "designUnorderedMultinom")
testthat::expect_equal(round(design1$power, 4), 0.9083)
testthat::expect_equal(design1$n, 40)
testthat::expect_equal(round(design1$effectsize, 4), 0.4466)
})
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testthat::test_that("getDesign: documented example returns stable design object", {
design1 <- getDesign(
beta = 0.2,
theta = -log(0.7),
kMax = 2,
informationRates = c(0.5, 1),
alpha = 0.025,
typeAlphaSpending = "sfOF",
typeBetaSpending = "sfP"
)
testthat::expect_s3_class(design1, "design")
testthat::expect_named(design1, c("byStageResults", "overallResults", "settings"))
# Printed summary reports power and max information; verify numerically.
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.8000)
testthat::expect_equal(round(design1$overallResults$information, 2), 71.97)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[1], 3), 2.963)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[2], 3), 1.969)
})
testthat::test_that("getDesign_multiarm: documented example returns stable multiarm object", {
design1 <- getDesign_multiarm(
beta = 0.1,
theta = c(0.3, 0.5),
M = 2,
r = 1.0,
kMax = 3,
informationRates = seq(1, 3) / 3,
alpha = 0.025,
typeAlphaSpending = "OF"
)
testthat::expect_s3_class(design1, "multiarm")
testthat::expect_named(design1,
c("byStageResults", "byLevelBounds", "overallResults", "settings"))
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9000)
testthat::expect_equal(round(design1$overallResults$information, 2), 47.15)
testthat::expect_equal(
round(design1$byStageResults$efficacyBounds, 3),
c(3.887, 2.748, 2.244)
)
})
testthat::test_that("getDesign_seamless: object contract and boundary dimensions", {
design1 <- getDesign_seamless(
beta = 0.1,
theta = c(0.3, 0.5),
M = 2,
r = 1.0,
K = 2,
informationRates = seq(1, 3) / 3,
alpha = 0.025,
typeAlphaSpending = "OF"
)
testthat::expect_s3_class(design1, "seamless")
testthat::expect_true("overallResults" %in% names(design1))
testthat::expect_true("byStageResults" %in% names(design1))
testthat::expect_true("settings" %in% names(design1))
testthat::expect_equal(nrow(design1$byStageResults), 3)
testthat::expect_true(all(design1$byStageResults$efficacyBounds > 0))
})
testthat::test_that("getDesign wrappers: invalid alpha is rejected", {
testthat::expect_error(
getDesign(beta = 0.2, theta = 0.4, kMax = 2, informationRates = c(0.5, 1), alpha = -0.1),
regexp = "alpha|significance"
)
testthat::expect_error(
getDesign_multiarm(beta = 0.1, theta = c(0.3, 0.5), M = 2, kMax = 3,
informationRates = seq(1, 3) / 3, alpha = -0.1),
regexp = "alpha|significance"
)
testthat::expect_error(
getDesign_seamless(beta = 0.1, theta = c(0.3, 0.5), M = 2, K = 2,
informationRates = seq(1, 3) / 3, alpha = -0.1),
regexp = "alpha|significance"
)
})
testthat::test_that("getDesignRiskDiff: Rd example numeric regression", {
design1 <- getDesignRiskDiff(
beta = 0.2,
n = NA,
pi1 = 0.1,
pi2 = 0.15,
kMax = 3,
alpha = 0.025,
typeAlphaSpending = "sfOF",
nullVariance = FALSE
)
testthat::expect_s3_class(design1, "designRiskDiff")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.8002)
testthat::expect_equal(round(design1$overallResults$numberOfSubjects, 0), 1384)
testthat::expect_equal(
round(design1$byStageResults$efficacyBounds, 3),
c(3.712, 2.511, 1.993)
)
})
testthat::test_that("getDesignOneProportion: Rd examples numeric regression", {
design1 <- getDesignOneProportion(
beta = 0.2,
n = NA,
piH0 = 0.15,
pi = 0.25,
kMax = 3,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
design2 <- getDesignOneProportion(
beta = 0.2,
n = NA,
piH0 = 0.15,
pi = 0.25,
normalApproximation = FALSE,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designOneProportion")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.8012)
testthat::expect_equal(round(design1$overallResults$numberOfSubjects, 0), 91)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[3], 3), 1.696)
testthat::expect_s3_class(design2, "designOneProportion")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.8097)
testthat::expect_equal(round(design2$overallResults$numberOfSubjects, 0), 110)
})
testthat::test_that("getDesignFisherExact: Rd example numeric regression", {
design1 <- getDesignFisherExact(
beta = 0.2,
pi1 = 0.5,
pi2 = 0.2,
alpha = 0.05
)
testthat::expect_s3_class(design1, "data.frame")
testthat::expect_equal(round(design1$power, 4), 0.8168)
testthat::expect_equal(design1$n, 87)
})
testthat::test_that("getDesignMeanDiff: Rd examples numeric regression", {
design1 <- getDesignMeanDiff(
beta = NA,
n = 456,
meanDiff = 9,
stDev = 32,
kMax = 5,
alpha = 0.025,
typeAlphaSpending = "sfOF",
typeBetaSpending = "sfP"
)
design2 <- getDesignMeanDiff(
beta = 0.1,
n = NA,
meanDiff = 0.3,
stDev = 1,
normalApproximation = FALSE,
alpha = 0.025
)
testthat::expect_s3_class(design1, "designMeanDiff")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.7421)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 456)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[1], 3), 4.883)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[5], 3), 2.031)
testthat::expect_s3_class(design2, "designMeanDiff")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9000)
testthat::expect_equal(round(design2$overallResults$numberOfSubjects, 0), 469)
})
testthat::test_that("getDesignWilcoxon: Rd examples numeric regression", {
p_larger <- pnorm((8 - 2) / sqrt(2 * 25^2))
design1 <- getDesignWilcoxon(
beta = 0.1,
n = NA,
pLarger = p_larger,
alpha = 0.025
)
design2 <- getDesignWilcoxon(
beta = 0.1,
n = NA,
pLarger = p_larger,
alpha = 0.025,
kMax = 3,
typeAlphaSpending = "sfOF"
)
testthat::expect_s3_class(design1, "designWilcoxon")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9002)
testthat::expect_equal(round(design1$overallResults$numberOfSubjects, 0), 772)
testthat::expect_s3_class(design2, "designWilcoxon")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9001)
testthat::expect_equal(round(design2$overallResults$numberOfSubjects, 0), 781)
testthat::expect_equal(
round(design2$byStageResults$efficacyBounds, 3),
c(3.713, 2.510, 1.993)
)
})
testthat::test_that("getDesignOddsRatio: Rd example numeric regression", {
design1 <- getDesignOddsRatio(
beta = 0.1,
n = NA,
pi1 = 0.5,
pi2 = 0.3,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designOddsRatio")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9012)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 210)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[1], 3), 1.645)
})
testthat::test_that("getDesignRiskRatio: Rd example numeric regression", {
design1 <- getDesignRiskRatio(
beta = 0.1,
n = NA,
pi1 = 0.5,
pi2 = 0.3,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designRiskRatio")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9008)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 207)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[1], 3), 1.645)
})
testthat::test_that("getDesignOneMean: Rd examples numeric regression", {
design1 <- getDesignOneMean(
beta = 0.1,
n = NA,
meanH0 = 7,
mean = 6,
stDev = 2.5,
kMax = 5,
alpha = 0.025,
typeAlphaSpending = "sfOF",
typeBetaSpending = "sfP"
)
design2 <- getDesignOneMean(
beta = 0.1,
n = NA,
meanH0 = 7,
mean = 6,
stDev = 2.5,
normalApproximation = FALSE,
alpha = 0.025
)
testthat::expect_s3_class(design1, "designOneMean")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9016)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 85)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[1], 3), 4.877)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[5], 3), 2.031)
testthat::expect_s3_class(design2, "designOneMean")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9016)
testthat::expect_equal(design2$overallResults$numberOfSubjects, 68)
testthat::expect_equal(round(design2$byStageResults$efficacyBounds[1], 3), 1.996)
})
testthat::test_that("getDesignANOVA: Rd example numeric regression", {
design1 <- getDesignANOVA(
beta = 0.1,
ngroups = 4,
means = c(1.5, 2.5, 2, 0),
stDev = 3.5,
allocationRatioPlanned = c(2, 2, 2, 1),
alpha = 0.05
)
testthat::expect_s3_class(design1, "designANOVA")
testthat::expect_equal(round(design1$power, 4), 0.9008)
testthat::expect_equal(design1$n, 279)
testthat::expect_equal(round(design1$effectsize, 4), 0.0516)
})
testthat::test_that("getDesignTwoOrdinal: Rd example numeric regression", {
design1 <- getDesignTwoOrdinal(
beta = 0.1,
ncats = 4,
pi1 = c(0.55, 0.3, 0.1),
pi2 = c(0.214, 0.344, 0.251),
alpha = 0.025
)
testthat::expect_s3_class(design1, "designTwoOrdinal")
testthat::expect_equal(round(design1$power, 4), 0.9030)
testthat::expect_equal(design1$n, 67)
testthat::expect_equal(round(design1$meanscore1, 4), 26.4055)
testthat::expect_equal(round(design1$meanscore2, 4), 40.5945)
})
testthat::test_that("getDesignOddsRatioEquiv: Rd example numeric regression", {
design1 <- getDesignOddsRatioEquiv(
beta = 0.2,
n = NA,
oddsRatioLower = 0.8,
oddsRatioUpper = 1.25,
pi1 = 0.12,
pi2 = 0.12,
kMax = 3,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
testthat::expect_s3_class(design1, "designOddsRatioEquiv")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.8000)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 6637)
testthat::expect_equal(round(design1$overallResults$information, 4), 175.2168)
testthat::expect_equal(
round(design1$byStageResults$efficacyBounds, 3),
c(3.200, 2.141, 1.695)
)
})
testthat::test_that("getDesignRiskRatioEquiv: Rd example numeric regression", {
design1 <- getDesignRiskRatioEquiv(
beta = 0.2,
n = NA,
riskRatioLower = 0.8,
riskRatioUpper = 1.25,
pi1 = 0.12,
pi2 = 0.12,
kMax = 3,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
testthat::expect_s3_class(design1, "designRiskRatioEquiv")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.8000)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 5140)
testthat::expect_equal(round(design1$overallResults$information, 4), 175.2273)
testthat::expect_equal(
round(design1$byStageResults$efficacyBounds, 3),
c(3.200, 2.141, 1.695)
)
})
testthat::test_that("getDesignOneRateExact: Rd examples numeric regression", {
design1 <- getDesignOneRateExact(
n = 525,
lambdaH0 = 0.049,
lambda = 0.012,
D = 0.5,
alpha = 0.025
)
design2 <- getDesignOneRateExact(
beta = 0.2,
lambdaH0 = 0.2,
lambda = 0.3,
D = 1,
alpha = 0.05
)
testthat::expect_s3_class(design1, "data.frame")
testthat::expect_equal(round(design1$power, 4), 0.9002)
testthat::expect_equal(round(design1$attainedAlpha, 4), 0.0117)
testthat::expect_equal(design1$n, 525)
testthat::expect_equal(design1$r, 5)
testthat::expect_s3_class(design2, "data.frame")
testthat::expect_equal(round(design2$power, 4), 0.8078)
testthat::expect_equal(round(design2$attainedAlpha, 4), 0.0427)
testthat::expect_equal(design2$n, 162)
testthat::expect_equal(design2$r, 43)
})
testthat::test_that("getDesignANOVAContrast: Rd example numeric regression", {
design1 <- getDesignANOVAContrast(
beta = 0.1,
ngroups = 4,
means = c(1.5, 2.5, 2, 0),
stDev = 3.5,
contrast = c(1, 1, 1, -3),
allocationRatioPlanned = c(2, 2, 2, 1),
alpha = 0.025
)
testthat::expect_s3_class(design1, "designANOVAContrast")
testthat::expect_equal(round(design1$power, 4), 0.9003)
testthat::expect_equal(design1$n, 265)
testthat::expect_equal(round(design1$effectsize, 4), 0.0400)
testthat::expect_equal(design1$meanContrast, 6)
})
testthat::test_that("getDesignRepeatedANOVA: Rd example numeric regression", {
design1 <- getDesignRepeatedANOVA(
beta = 0.1,
ngroups = 4,
means = c(1.5, 2.5, 2, 0),
stDev = 5,
corr = 0.2,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designRepeatedANOVA")
testthat::expect_equal(round(design1$power, 4), 0.9027)
testthat::expect_equal(design1$n, 83)
testthat::expect_equal(round(design1$effectsize, 3), 0.175)
})
testthat::test_that("getDesignMeanDiffEquiv: Rd examples numeric regression", {
design1 <- getDesignMeanDiffEquiv(
beta = 0.1,
n = NA,
meanDiffLower = -1.3,
meanDiffUpper = 1.3,
meanDiff = 0,
stDev = 2.2,
kMax = 4,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
design2 <- getDesignMeanDiffEquiv(
beta = 0.1,
n = NA,
meanDiffLower = -1.3,
meanDiffUpper = 1.3,
meanDiff = 0,
stDev = 2.2,
normalApproximation = FALSE,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designMeanDiffEquiv")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9024)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 128)
testthat::expect_equal(round(design1$overallResults$information, 4), 6.6116)
testthat::expect_equal(
round(design1$byStageResults$efficacyBounds, 3),
c(3.750, 2.540, 2.016, 1.720)
)
testthat::expect_s3_class(design2, "designMeanDiffEquiv")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9018)
testthat::expect_equal(design2$overallResults$numberOfSubjects, 126)
testthat::expect_equal(round(design2$byStageResults$efficacyBounds[1], 3), 1.657)
})
testthat::test_that("getDesignAgreement: Rd example numeric regression", {
design1 <- getDesignAgreement(
beta = 0.2,
n = NA,
ncats = 4,
kappaH0 = 0.4,
kappa = 0.6,
p1 = c(0.1, 0.2, 0.3, 0.4),
p2 = c(0.15, 0.2, 0.24, 0.41),
rounding = TRUE,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designAgreement")
testthat::expect_equal(round(design1$power, 4), 0.8006)
testthat::expect_equal(design1$n, 82)
})
testthat::test_that("getDesignEquiv: Rd example numeric regression", {
design1 <- getDesignEquiv(
beta = 0.2,
thetaLower = log(0.8),
thetaUpper = log(1.25),
kMax = 2,
informationRates = c(0.5, 1),
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
testthat::expect_s3_class(design1, "designEquiv")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.8000)
testthat::expect_equal(round(design1$overallResults$information, 4), 173.2257)
})
testthat::test_that("getDesignLogistic: Rd example numeric regression", {
x1 <- c(5, 10, 15, 20)
px1 <- c(0.2, 0.3, 0.3, 0.2)
x2 <- c(2, 4, 6)
px2 <- c(0.4, 0.4, 0.2)
nbins <- 10
x3 <- qnorm(((1:nbins) - 0.5) / nbins) * 2 + 4
px3 <- rep(1 / nbins, nbins)
nconfigs <- length(x1) * length(x2) * length(x3)
x <- expand.grid(x3 = x3, x2 = x2, x1 = x1)
x <- as.matrix(x[, ncol(x):1])
pconfigs <- as.numeric(px1 %x% px2 %x% px3)
design1 <- getDesignLogistic(
beta = 0.1,
ncovariates = 3,
nconfigs = nconfigs,
x = x,
pconfigs = pconfigs,
oddsratios = c(1.2^(1/5), 1.4, 1.3),
responseprob = 0.25,
alpha = 0.1
)
testthat::expect_s3_class(design1, "designLogistic")
testthat::expect_equal(round(design1$power, 4), 0.9002)
testthat::expect_equal(design1$n, 1369)
testthat::expect_equal(round(design1$effectsize, 4), 0.0063)
})
testthat::test_that("getDesignMeanRatio: Rd example numeric regression", {
design1 <- getDesignMeanRatio(
beta = 0.1,
n = NA,
meanRatio = 1.25,
CV = 0.35,
kMax = 3,
alpha = 0.025,
typeAlphaSpending = "sfOF"
)
testthat::expect_s3_class(design1, "designMeanRatio")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9009)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 99)
})
testthat::test_that("getDesignOneMultinom: Rd example numeric regression", {
design1 <- getDesignOneMultinom(
beta = 0.1,
ncats = 3,
piH0 = c(0.25, 0.25),
pi = c(0.3, 0.4),
alpha = 0.05
)
testthat::expect_s3_class(design1, "designOneMultinom")
testthat::expect_equal(round(design1$power, 4), 0.9030)
testthat::expect_equal(design1$n, 71)
})
testthat::test_that("getDesignMeanRatioEquiv: Rd examples numeric regression", {
design1 <- getDesignMeanRatioEquiv(
beta = 0.1,
n = NA,
meanRatioLower = 0.8,
meanRatioUpper = 1.25,
meanRatio = 1,
CV = 0.35,
kMax = 4,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
design2 <- getDesignMeanRatioEquiv(
beta = 0.1,
n = NA,
meanRatioLower = 0.8,
meanRatioUpper = 1.25,
meanRatio = 1,
CV = 0.35,
normalApproximation = FALSE,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designMeanRatioEquiv")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9033)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 104)
testthat::expect_equal(round(design1$overallResults$information, 4), 224.9946)
testthat::expect_equal(
round(design1$byStageResults$efficacyBounds, 3),
c(3.750, 2.540, 2.016, 1.720)
)
testthat::expect_s3_class(design2, "designMeanRatioEquiv")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9005)
testthat::expect_equal(design2$overallResults$numberOfSubjects, 102)
testthat::expect_equal(round(design2$byStageResults$efficacyBounds[1], 3), 1.660)
})
testthat::test_that("getDesignRiskDiffEquiv: Rd example numeric regression", {
design1 <- getDesignRiskDiffEquiv(
beta = 0.2,
n = NA,
riskDiffLower = -0.1,
riskDiffUpper = 0.1,
pi1 = 0.12,
pi2 = 0.12,
kMax = 3,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
testthat::expect_s3_class(design1, "designRiskDiffEquiv")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.8007)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 369)
testthat::expect_equal(round(design1$overallResults$information, 4), 873.5795)
testthat::expect_equal(
round(design1$byStageResults$efficacyBounds, 3),
c(3.200, 2.141, 1.695)
)
})
testthat::test_that("getDesignRepeatedANOVAContrast: Rd example numeric regression", {
design1 <- getDesignRepeatedANOVAContrast(
beta = 0.1,
ngroups = 4,
means = c(1.5, 2.5, 2, 0),
stDev = 5,
corr = 0.2,
contrast = c(1, 1, 1, -3) / 3,
alpha = 0.025
)
testthat::expect_s3_class(design1, "designRepeatedANOVAContrast")
testthat::expect_equal(round(design1$power, 4), 0.9012)
testthat::expect_equal(design1$n, 71)
testthat::expect_equal(round(design1$effectsize, 3), 0.150)
testthat::expect_equal(design1$meanContrast, 2)
})
testthat::test_that("getDesignMeanDiffCarryover: Rd example numeric regression", {
design1 <- getDesignMeanDiffCarryover(
beta = 0.2,
n = NA,
meanDiff = 0.5,
stDev = 1,
design = matrix(c(1, 4, 2, 3,
2, 1, 3, 4,
3, 2, 4, 1,
4, 3, 1, 2),
4, 4, byrow = TRUE),
alpha = 0.025
)
testthat::expect_s3_class(design1, "designMeanDiffCarryover")
testthat::expect_equal(round(design1$power, 4), 0.8015)
testthat::expect_equal(design1$numberOfSubjects, 70)
})
testthat::test_that("getDesignMeanDiffCarryoverEquiv: Rd example numeric regression", {
design1 <- getDesignMeanDiffCarryoverEquiv(
beta = 0.2,
n = NA,
meanDiffLower = -1.3,
meanDiffUpper = 1.3,
meanDiff = 0,
stDev = 2.2,
design = matrix(c(1, 4, 2, 3,
2, 1, 3, 4,
3, 2, 4, 1,
4, 3, 1, 2),
4, 4, byrow = TRUE),
alpha = 0.025
)
testthat::expect_s3_class(design1, "designMeanDiffCarryoverEquiv")
testthat::expect_equal(round(design1$power, 4), 0.8011)
testthat::expect_equal(design1$numberOfSubjects, 67)
})
testthat::test_that("getDesignMeanDiffXOEquiv: Rd examples numeric regression", {
design1 <- getDesignMeanDiffXOEquiv(
beta = 0.1,
n = NA,
meanDiffLower = -1.3,
meanDiffUpper = 1.3,
meanDiff = 0,
stDev = 2.2,
kMax = 4,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
design2 <- getDesignMeanDiffXOEquiv(
beta = 0.1,
n = NA,
meanDiffLower = -1.3,
meanDiffUpper = 1.3,
meanDiff = 0,
stDev = 2.2,
normalApproximation = FALSE,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designMeanDiffXOEquiv")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9024)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 64)
testthat::expect_s3_class(design2, "designMeanDiffXOEquiv")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9033)
testthat::expect_equal(design2$overallResults$numberOfSubjects, 64)
})
testthat::test_that("getDesignMeanDiffXO: Rd example numeric regression", {
design1 <- getDesignMeanDiffXO(
beta = 0.2,
n = NA,
meanDiff = 75,
stDev = 150,
normalApproximation = FALSE,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designMeanDiffXO")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.8009)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 51)
})
testthat::test_that("getDesignMeanRatioXO: Rd example numeric regression", {
design1 <- getDesignMeanRatioXO(
beta = 0.1,
n = NA,
meanRatio = 1.25,
CV = 0.25,
alpha = 0.05,
normalApproximation = FALSE
)
testthat::expect_s3_class(design1, "designMeanRatioXO")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9078)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 23)
})
testthat::test_that("getDesignMeanRatioXOEquiv: Rd examples numeric regression", {
design1 <- getDesignMeanRatioXOEquiv(
beta = 0.1,
n = NA,
meanRatioLower = 0.8,
meanRatioUpper = 1.25,
meanRatio = 1,
CV = 0.35,
kMax = 4,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
design2 <- getDesignMeanRatioXOEquiv(
beta = 0.1,
n = NA,
meanRatioLower = 0.8,
meanRatioUpper = 1.25,
meanRatio = 1,
CV = 0.35,
normalApproximation = FALSE,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designMeanRatioXOEquiv")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9033)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 52)
testthat::expect_s3_class(design2, "designMeanRatioXOEquiv")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9024)
testthat::expect_equal(design2$overallResults$numberOfSubjects, 52)
})
testthat::test_that("getDesignOrderedBinom: Rd example numeric regression", {
design1 <- getDesignOrderedBinom(
beta = 0.1,
ngroups = 3,
pi = c(0.1, 0.25, 0.5),
alpha = 0.05
)
testthat::expect_s3_class(design1, "designOrderedBinom")
testthat::expect_equal(round(design1$power, 4), 0.9011)
testthat::expect_equal(design1$n, 75)
})
testthat::test_that("getDesignPairedMeanDiff: Rd examples numeric regression", {
design1 <- getDesignPairedMeanDiff(
beta = 0.1,
n = NA,
pairedDiffH0 = 0,
pairedDiff = -2,
stDev = 5,
kMax = 5,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
design2 <- getDesignPairedMeanDiff(
beta = 0.1,
n = NA,
pairedDiffH0 = 0,
pairedDiff = -2,
stDev = 5,
normalApproximation = FALSE,
alpha = 0.025
)
testthat::expect_s3_class(design1, "designPairedMeanDiff")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9033)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 56)
testthat::expect_s3_class(design2, "designPairedMeanDiff")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9016)
testthat::expect_equal(design2$overallResults$numberOfSubjects, 68)
})
testthat::test_that("getDesignPairedMeanDiffEquiv: Rd examples numeric regression", {
design1 <- getDesignPairedMeanDiffEquiv(
beta = 0.1,
n = NA,
pairedDiffLower = -1.3,
pairedDiffUpper = 1.3,
pairedDiff = 0,
stDev = 2.2,
kMax = 4,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
design2 <- getDesignPairedMeanDiffEquiv(
beta = 0.1,
n = NA,
pairedDiffLower = -1.3,
pairedDiffUpper = 1.3,
pairedDiff = 0,
stDev = 2.2,
normalApproximation = FALSE,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designPairedMeanDiffEquiv")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9024)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 32)
testthat::expect_s3_class(design2, "designPairedMeanDiffEquiv")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9064)
testthat::expect_equal(design2$overallResults$numberOfSubjects, 33)
})
testthat::test_that("getDesignMeanDiffMMRM: Rd example numeric regression", {
design1 <- getDesignMeanDiffMMRM(
beta = 0.1,
meanDiff = 0.5,
k = 2,
t = c(1, 2),
accrualIntensity = 40,
accrualDuration = 1
)
testthat::expect_s3_class(design1, "designMeanDiffMMRM")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9015)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 169)
})
testthat::test_that("getDesignOneSlope: Rd example numeric regression", {
design1 <- getDesignOneSlope(
beta = 0.1,
n = NA,
slope = 1,
stDev = 1,
stDevCovariate = 1,
alpha = 0.025
)
testthat::expect_s3_class(design1, "designOneSlope")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9126)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 11)
})
testthat::test_that("getDesignPairedMeanRatio: Rd example numeric regression", {
design1 <- getDesignPairedMeanRatio(
beta = 0.1,
n = NA,
pairedRatio = 1.2,
CV = 0.35,
alpha = 0.05,
normalApproximation = FALSE
)
testthat::expect_s3_class(design1, "designPairedMeanRatio")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9069)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 32)
})
testthat::test_that("getDesignPairedMeanRatioEquiv: Rd examples numeric regression", {
design1 <- getDesignPairedMeanRatioEquiv(
beta = 0.1,
n = NA,
pairedRatioLower = 0.8,
pairedRatioUpper = 1.25,
pairedRatio = 1,
CV = 0.35,
kMax = 4,
alpha = 0.05,
typeAlphaSpending = "sfOF"
)
design2 <- getDesignPairedMeanRatioEquiv(
beta = 0.1,
n = NA,
pairedRatioLower = 0.8,
pairedRatioUpper = 1.25,
pairedRatio = 1,
CV = 0.35,
normalApproximation = FALSE,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designPairedMeanRatioEquiv")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9029)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 26)
testthat::expect_s3_class(design2, "designPairedMeanRatioEquiv")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9061)
testthat::expect_equal(design2$overallResults$numberOfSubjects, 27)
})
testthat::test_that("getDesignRiskDiffExact: Rd example numeric regression", {
design1 <- getDesignRiskDiffExact(
n = 50,
pi1 = 0.6,
pi2 = 0.25,
alpha = 0.025
)
testthat::expect_s3_class(design1, "data.frame")
testthat::expect_equal(design1$power, 0.694611217040014)
testthat::expect_equal(design1$n, 50)
})
testthat::test_that("getDesignRiskDiffExactEquiv: Rd example numeric regression", {
design1 <- getDesignRiskDiffExactEquiv(
n = 200,
riskDiffLower = -0.2,
riskDiffUpper = 0.2,
pi1 = 0.775,
pi2 = 0.775,
alpha = 0.05
)
testthat::expect_s3_class(design1, "data.frame")
testthat::expect_equal(round(design1$power, 4), 0.9147)
testthat::expect_equal(design1$n, 200)
})
testthat::test_that("getDesignRiskRatioExact: Rd example numeric regression", {
design1 <- getDesignRiskRatioExact(
beta = 0.2,
riskRatioH0 = 0.7,
pi1 = 0.95,
pi2 = 0.95,
alpha = 0.025
)
testthat::expect_s3_class(design1, "data.frame")
testthat::expect_equal(round(design1$power, 4), 0.8573)
testthat::expect_equal(design1$n, 39)
})
testthat::test_that("getDesignRiskRatioExactEquiv: Rd example numeric regression", {
design1 <- getDesignRiskRatioExactEquiv(
n = 200,
riskRatioLower = 0.8,
riskRatioUpper = 1.25,
pi1 = 0.775,
pi2 = 0.775,
alpha = 0.05
)
testthat::expect_s3_class(design1, "data.frame")
testthat::expect_equal(round(design1$power, 4), 0.7514)
testthat::expect_equal(design1$n, 200)
})
testthat::test_that("getDesignRiskRatioFM: Rd example numeric regression", {
design1 <- getDesignRiskRatioFM(
beta = 0.2,
riskRatioH0 = 1.3,
pi1 = 0.125,
pi2 = 0.125,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designRiskRatioFM")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.8001)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 2531)
})
testthat::test_that("getDesignPairedPropMcNemar: Rd examples numeric regression", {
design1 <- getDesignPairedPropMcNemar(
beta = 0.1,
n = NA,
pDiscordant = 0.16,
riskDiff = 0.1,
alpha = 0.025
)
design2 <- getDesignPairedPropMcNemar(
beta = 0.1,
n = NA,
pDiscordant = 0.16,
riskDiff = 0.1,
alpha = 0.025,
kMax = 3,
typeAlphaSpending = "sfOF"
)
testthat::expect_s3_class(design1, "designPairedPropMcNemar")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9001)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 164)
testthat::expect_s3_class(design2, "designPairedPropMcNemar")
testthat::expect_equal(round(design2$overallResults$overallReject, 4), 0.9016)
testthat::expect_equal(design2$overallResults$numberOfSubjects, 167)
testthat::expect_equal(
round(design2$byStageResults$efficacyBounds, 3),
c(3.698, 2.516, 1.993)
)
})
testthat::test_that("getDesignSlopeDiff: Rd example numeric regression", {
design1 <- getDesignSlopeDiff(
beta = 0.1,
n = NA,
slopeDiff = -0.5,
stDev = 10,
stDevCovariate = 6,
normalApproximation = FALSE,
alpha = 0.025
)
testthat::expect_s3_class(design1, "designSlopeDiff")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.9000)
testthat::expect_equal(design1$overallResults$numberOfSubjects, 469)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[1], 3), 1.965)
})
testthat::test_that("getDesignSlopeDiffMMRM: Rd example numeric regression", {
design1 <- getDesignSlopeDiffMMRM(
beta = 0.2,
slopeDiff = log(1.15) / 52,
stDev = sqrt(.182),
stDevIntercept = sqrt(.238960),
stDevSlope = sqrt(.000057),
corrInterceptSlope = .003688 / sqrt(.238960 * .000057),
w = 8,
N = 10000,
accrualIntensity = 15,
gamma1 = 1 / (4.48 * 52),
gamma2 = 1 / (4.48 * 52),
accrualDuration = NA,
followupTime = 8,
alpha = 0.025
)
testthat::expect_s3_class(design1, "designSlopeDiffMMRM")
testthat::expect_equal(round(design1$overallResults$overallReject, 4), 0.8004)
testthat::expect_equal(round(design1$overallResults$information, 0), 1087517)
testthat::expect_equal(round(design1$overallResults$numberOfSubjects, 0), 1013)
testthat::expect_equal(round(design1$overallResults$studyDuration, 4), 75.5333)
testthat::expect_equal(round(design1$overallResults$accrualDuration, 4), 67.5333)
testthat::expect_equal(round(design1$byStageResults$efficacyBounds[1], 3), 1.960)
})
testthat::test_that("getDesignTwoMultinom: Rd example numeric regression", {
design1 <- getDesignTwoMultinom(
beta = 0.1,
ncats = 3,
pi1 = c(0.3, 0.35),
pi2 = c(0.2, 0.3),
alpha = 0.05
)
testthat::expect_s3_class(design1, "designTwoMultinom")
testthat::expect_equal(round(design1$power, 4), 0.9000)
testthat::expect_equal(design1$n, 503)
testthat::expect_equal(round(design1$effectsize, 4), 0.0252)
})
testthat::test_that("getDesignTwoWayANOVA: Rd example numeric regression", {
design1 <- getDesignTwoWayANOVA(
beta = 0.1,
nlevelsA = 2,
nlevelsB = 2,
means = matrix(c(0.5, 4.7, 0.4, 6.9), 2, 2, byrow = TRUE),
stDev = 2,
alpha = 0.05
)
testthat::expect_s3_class(design1, "designTwoWayANOVA")
testthat::expect_equal(design1$powerdf$n[1], 156)
testthat::expect_equal(round(design1$powerdf$powerA[1], 4), 0.9028)
testthat::expect_equal(round(design1$powerdf$powerB[1], 4), 1.0000)
testthat::expect_equal(round(design1$powerdf$powerAB[1], 4), 0.9461)
testthat::expect_equal(round(design1$effectsizeAB, 4), 0.0827)
})
testthat::test_that("getDesignUnorderedBinom: Rd example numeric regression", {
design1 <- getDesignUnorderedBinom(
beta = 0.1,
ngroups = 3,
pi = c(0.1, 0.25, 0.5),
alpha = 0.05
)
testthat::expect_s3_class(design1, "designUnorderedBinom")
testthat::expect_equal(round(design1$power, 4), 0.9020)
testthat::expect_equal(design1$n, 95)
testthat::expect_equal(round(design1$effectsize, 4), 0.1341)
})
testthat::test_that("getDesignUnorderedMultinom: Rd example numeric regression", {
design1 <- getDesignUnorderedMultinom(
beta = 0.1,
ngroups = 3,
ncats = 4,
pi = matrix(c(0.230, 0.320, 0.272,
0.358, 0.442, 0.154,
0.142, 0.036, 0.039),
3, 3, byrow = TRUE),
allocationRatioPlanned = c(2, 2, 1),
alpha = 0.05
)
testthat::expect_s3_class(design1, "designUnorderedMultinom")
testthat::expect_equal(round(design1$power, 4), 0.9083)
testthat::expect_equal(design1$n, 40)
testthat::expect_equal(round(design1$effectsize, 4), 0.4466)
})
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