tests/testthat/test-ADTreatSel.r
In medianasoft/MedianaDesigner: Power and Sample Size Calculations for Clinical Trials
commonNSim = 50
isTestMultiCore = FALSE
# Normal case parameters
normalCase = list(
# Number of trial arms
narms = 3,
# Sample size
sample_size = c(120, 120, 120),
# Primary endpoint's type
endpoint_type = "Normal",
# Direction of favorable outcome (Higher or Lower)
# Default: Higher
#direction = "Higher",
# Mean and SD in the control arm
control_mean = 0,
control_sd = 1,
# Mean and SD in the treatment arm
treatment_mean = c(0.3, 0.3),
treatment_sd = c(1, 1),
# Information fractions at IA1, IA2, FA
info_frac = c(0.4, 0.6, 1.0),
# Futility threshold for conditional power at IA1
futility_threshold = 0.1,
# Number of selected treatments
treatment_count = 1,
# Multiple testing procedure (Bonferroni, Holm or Hochberg)
mult_test = "Bonferroni",
# Dropout rate at the end of the treatment period
dropout_rate = 0.05,
# One-sided Type I error rate
alpha = 0.025,
# Number of simulations
nsims = commonNSim
)
# Binary case parameters
binaryCase = list(
# Endpoint type
endpoint_type = "Binary",
# Direction of favorable outcome (Higher or Lower)
# Default: Higher
direction = "Higher",
# Number of enrolled patients (control, three treatments)
sample_size = c(150, 150, 150, 150),
# Patient dropout rate
dropout_rate = 0.1,
# Response rate in the control arm
control_rate = 0.1,
# Response rates in the treatment arms
treatment_rate = c(0.25, 0.25, 0.25),
# Information fractions at IA1, IA2, FA
info_frac = c(0.4, 0.6, 1),
# Futility threshold for conditional power at IA1
futility_threshold = 0.15,
# Number of selected treatments
treatment_count = 1,
# Multiple testing procedure (Bonferroni, Holm or Hochberg)
mult_test = "Bonferroni",
# One-sided alpha level
alpha = 0.025,
# Number of simulations
nsims = commonNSim
)
binaryCase2 = list(
# Endpoint type
endpoint_type = "Binary",
# Number of enrolled patients (placebo and four regimens)
sample_size = c(90, 90, 90, 90, 90),
# Response rate in the control arm
control_rate = 0.1,
# Response rates in the regimen arms
treatment_rate = c(0.30, 0.30, 0.35, 0.35),
# Information fractions at Interim analysis 1, Interim analysis 2, Final analysis
info_frac = c(0.2, 0.5, 1),
# Futility threshold for conditional power at Interim analysis 1
futility_threshold = 0.3,
# Patient dropout rate at the end of the 26-week treatment period
dropout_rate = 0.15,
# Number of treatments to be selected at the second interim analysis
treatment_count = 1,
# Multiple testing procedure to be used in the trial
mult_test = "Hochberg",
# One-sided alpha level
alpha = 0.025,
# Number of simulations
nsims = commonNSim
)
# Time-to-event case parameters
timeToEventCase = list(
# Endpoint type
endpoint_type = "Time-to-event",
# Direction of favorable outcome (Higher or Lower)
# Default: Higher
direction = "Higher",
# Number of enrolled patients (control, two treatments)
sample_size = c(180, 180, 180),
# Annual patient dropout rate
dropout_rate = 0.05,
# Median time in the control arm
control_time = 7.5,
# Median times in the treatment arms
treatment_time = c(10.5, 10.5),
# Target event count at FA
event_count = 450,
# Information fractions at IA1, IA2, FA
info_frac = c(0.4, 0.6, 1),
# Futility threshold for conditional power at IA1
futility_threshold = 0.1,
# Number of selected treatments
treatment_count = 1,
# Multiple testing procedure (Bonferroni, Holm or Hochberg)
mult_test = "Bonferroni",
# Enrollment period
enrollment_period = 24,
# Median enrollment time
enrollment_parameter = 18,
# One-sided alpha level
alpha = 0.025,
# Number of simulations
nsims = commonNSim
)
context("ADTreatSel - Success runs")
checkExpectationsForNormalCase = function(results) {
expect_s3_class(results, "ADTreatSelResults")
expect_type( results$sim_results, "double")
expect_length(results$sim_results, 7 * results$parameters$nsims)
sim_summary = results$sim_summary
# print(sim_summary)
expect_type( sim_summary, "list")
expect_equal( sim_summary$ad_power, 0.641, tolerance=0.1)
expect_equal( sim_summary$overall_futility, 0.076, tolerance=0.1)
expect_is( sim_summary$select, "numeric")
expect_length( sim_summary$select, 2)
expect_equal(unname(sim_summary$select[1]), 0.453, tolerance=0.1)
expect_equal(unname(sim_summary$select[2]), 0.453, tolerance=0.1)
expect_is( sim_summary$futility, "numeric")
expect_length( sim_summary$futility, 2)
expect_equal(unname(sim_summary$futility[1]), 0.190, tolerance=0.1)
expect_equal(unname(sim_summary$futility[2]), 0.186, tolerance=0.1)
expect_is( sim_summary$trad_power, "numeric")
expect_length( sim_summary$trad_power, 2)
expect_equal(unname(sim_summary$trad_power[1]), 0.596, tolerance=0.1)
expect_equal(unname(sim_summary$trad_power[2]), 0.586, tolerance=0.1)
}
test_that("Success run ADTreatSel with Normal case (single core)", {
# Success run
results = ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
info_frac = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
# use default
#dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
# use default
#nsims = normalCase$nsims
# Run one with random seek value
random_seed = 49283
)
)
checkExpectationsForNormalCase(results)
# Check for report generation
ADTreatSelReportDoc(results)
})
if (isTestMultiCore) {
test_that("Success run ADTreatSel with Normal case (two cores)", {
# Success run
params = normalCase
params$ncores = 2
results = ADTreatSel(params)
checkExpectationsForNormalCase(results)
})
}
test_that("Success run ADTreatSel with Binary case", {
# Success run
results = ADTreatSel(
list(
endpoint_type = binaryCase$endpoint_type,
sample_size = binaryCase$sample_size,
dropout_rate = binaryCase$dropout_rate,
control_rate = binaryCase$control_rate,
treatment_rate = binaryCase$treatment_rate,
info_frac = binaryCase$info_frac,
futility_threshold = binaryCase$futility_threshold,
treatment_count = binaryCase$treatment_count,
mult_test = binaryCase$mult_test,
# use default
#alpha = binaryCase$alpha,
nsims = binaryCase$nsims
)
)
expect_is(results, "ADTreatSelResults")
expect_type( results$sim_results, "double")
expect_length(results$sim_results, 10 * binaryCase$nsims)
expect_type( results$sim_summary, "list")
expect_true(abs(results$sim_summary$ad_power - 0.8) < 0.2)
expect_true(abs(results$sim_summary$overall_futility - 0.1) < 0.1)
expect_is( results$sim_summary$select, "numeric")
expect_length( results$sim_summary$select, 3)
expect_equivalent(results$sim_summary$select, c(0.35, 0.33, 0.42), tolerance=0.1)
expect_is( results$sim_summary$futility, "numeric")
expect_length( results$sim_summary$futility, 3)
expect_true(abs(results$sim_summary$futility[1] - 0.1) < 0.1)
expect_true(abs(results$sim_summary$futility[2] - 0.1) < 0.1)
expect_true(abs(results$sim_summary$futility[3] - 0.1) < 0.1)
expect_is( results$sim_summary$trad_power, "numeric")
expect_length( results$sim_summary$trad_power, 3)
expect_true(abs(results$sim_summary$trad_power[1] - 0.8) < 0.2)
expect_true(abs(results$sim_summary$trad_power[2] - 0.8) < 0.2)
expect_true(abs(results$sim_summary$trad_power[3] - 0.8) < 0.2)
# Check for report generation
ADTreatSelReportDoc(results)
})
checkExpectationsForBinaryCase2 = function(res) {
expect_s3_class(res, "ADTreatSelResults")
# check sim_results
expect_length(res$sim_results, 13 * res$parameters$nsims)
# check sim_summary
expect_equal(res$sim_summary$ad_power, 0.9175, tolerance=0.1)
expect_equal(res$sim_summary$overall_futility, 0.0179, tolerance=0.1)
expect_equivalent(res$sim_summary$trad_power, c(0.7133, 0.7175, 0.8435, 0.8375), tolerance=0.1)
expect_equivalent(res$sim_summary$select, c(0.1612, 0.1639, 0.3867, 0.3801), tolerance=0.2)
expect_equivalent(res$sim_summary$futility, c(0.2326, 0.2253, 0.1424, 0.1468), tolerance=0.2)
}
test_that("Success run ADTreatSel with Binary case 2 (one core)", {
# Success run
params = binaryCase2
params$sims = 100
# params$ncores = 1
res = ADTreatSel(params)
checkExpectationsForBinaryCase2(res)
})
test_that("Success run ADTreatSel with Binary case 2 (two cores)", {
# Success run
params = binaryCase2
params$sims = 100
params$ncores = 2
res = ADTreatSel(params)
checkExpectationsForBinaryCase2(res)
})
test_that("Success run ADTreatSel with Time-to-event case", {
# Success run
results = ADTreatSel(timeToEventCase)
expect_is(results, "ADTreatSelResults")
expect_type( results$sim_results, "double")
expect_length(results$sim_results, 7 * timeToEventCase$nsims)
expect_type( results$sim_summary, "list")
expect_true(abs(results$sim_summary$ad_power - 0.8) < 0.2)
expect_true(abs(results$sim_summary$overall_futility - 0.1) < 0.1)
expect_is( results$sim_summary$select, "numeric")
expect_length( results$sim_summary$select, 2)
expect_true(abs(results$sim_summary$select[1] - 0.49) < 0.1)
expect_true(abs(results$sim_summary$select[2] - 0.47) < 0.1)
expect_is( results$sim_summary$futility, "numeric")
expect_length( results$sim_summary$futility, 2)
expect_true(abs(results$sim_summary$futility[1] - 0.1) < 0.1)
expect_true(abs(results$sim_summary$futility[2] - 0.1) < 0.1)
expect_is( results$sim_summary$trad_power, "numeric")
expect_length( results$sim_summary$trad_power, 2)
expect_true(abs(results$sim_summary$trad_power[1] - 0.8) < 0.2)
expect_true(abs(results$sim_summary$trad_power[2] - 0.8) < 0.2)
# Check for report generation
ADTreatSelReportDoc(results)
})
test_that("Success run ADTreatSel with Normal case and short sample_size vector", {
# Success run
results = ADTreatSel(
list(
narms = normalCase$narms,
sample_size = c(120, 120), #normalCase$sample_size = c(120, 120, 120)
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = c(0.3), # treatment_mean = c(0.3, 0.3),
treatment_sd = c(1), # treatment_sd = c(1, 1),
info_frac = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
)
expect_is(results, "ADTreatSelResults")
expect_type( results$sim_results, "double")
expect_length(results$sim_results, 4 * normalCase$nsims)
expect_type( results$sim_summary, "list")
expect_true(abs(results$sim_summary$ad_power - 0.5) < 0.3)
expect_true(abs(results$sim_summary$overall_futility - 0.2) < 0.1)
expect_is( results$sim_summary$select, "numeric")
expect_length( results$sim_summary$select, 1)
expect_true(abs(results$sim_summary$select[1] - 0.7) < 0.2)
expect_is( results$sim_summary$futility, "numeric")
expect_length( results$sim_summary$futility, 1)
expect_true(abs(results$sim_summary$futility[1] - 0.2) < 0.1)
expect_is( results$sim_summary$trad_power, "numeric")
expect_length( results$sim_summary$trad_power, 1)
expect_true(abs(results$sim_summary$trad_power[1] - 0.5) < 0.2)
# Check for report generation
ADTreatSelReportDoc(results)
GenerateReport(results, tempfile(fileext = ".docx"))
})
test_that("Success run ADTreatSel with Lower direction", {
# Success run
results = ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
direction = "Lower",
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
info_frac = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
)
expect_is(results, "ADTreatSelResults")
expect_type( results$sim_results, "double")
expect_length(results$sim_results, 7 * normalCase$nsims)
expect_type( results$sim_summary, "list")
expect_is( results$sim_summary$select, "numeric")
expect_is( results$sim_summary$futility, "numeric")
expect_is( results$sim_summary$trad_power, "numeric")
# Check for report generation
ADTreatSelReportDoc(results)
})
context("ADTreatSel - Error checks")
test_that("Input parameters errors check ADTreatSel", {
# Errors check
expect_error(
ADTreatSel(
c("Not a list")
),
info = "Checking for wrong parameters collection type"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
# missing
#endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
info_frac = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for missing endpoint type"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
# wrong
endpoint_type = "SomeType", #normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
info_frac = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
dropout_rate = normalCase$dropout_rate,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for missing endpoint type"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
endpoint_type = normalCase$endpoint_type,
# wrong
direction = "Wrong",
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
info_frac = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for wrong direction"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
# missing
#info_frac = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for missing information fractions at IA1, IA2, FA"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
# wrong (IA1 >= IA2)
info_frac = c(0.8, 0.6, 1.0), # normalCase$info_frac == c(0.4, 0.6, 1.0),
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for wrong information fraction (IA1 must be < IA2)"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
# wrong (IA2 >= FA)
info_frac = c(0.4, 1.0, 0.9), # normalCase$info_frac == c(0.4, 0.6, 1.0),
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for wrong information fraction (IA2 must be < FA)"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
# wrong (FA != 1)
info_frac = c(0.4, 0.6, 0.9), # normalCase$info_frac == c(0.4, 0.6, 1.0),
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for wrong information fraction (FA must be 1)"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
# wrong
info_frac = c(0.4, 0.6), # c(0.4, 0.6, 1.0) = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for wrong information fractions at IA1, IA2, FA (incorrect length)"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
# wrong
info_frac = c(0, 0.6, 1.0), # c(0.4, 0.6, 1.0) = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for wrong information fractions at IA1, IA2, FA (value <= 0)"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
# wrong
info_frac = c(0.4, 0.6, 1.1), # c(0.4, 0.6, 1.0) = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for wrong information fractions at IA1, IA2, FA (value > 1)"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
# wrong
info_frac = c(0.4, 0.6, "1.0"), # c(0.4, 0.6, 1.0) = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for wrong information fractions at IA1, IA2, FA (value not a number)"
)
# Universal parameter check func
testParameterErrors = function(params, paramName, paramDesc,
checkMissing = TRUE, checkWrong = NA, checkSize = TRUE, checkMin = NA, checkMax = NA) {
func = ADTreatSel
paramDesc = paste0(paramDesc, " (", paramName, ")")
if (!is.null(params$endpoint_type))
paramDesc = paste0(params$endpoint_type, ": ", paramDesc)
# Missing
if (checkMissing) {
testParams = params
testParams[paramName] <- NULL
expect_error(func(testParams),
info = paste0("Checking for missing ", paramDesc))
}
# Wrong
if (!is.null(checkWrong) && !is.na(checkWrong)) {
testParams = params
testParams[paramName] <- checkWrong
expect_error(func(testParams),
info = paste0("Checking for wrong ", paramDesc))
}
# Check size
if (checkSize) {
testParams = params
testParams[[paramName]] <- append(testParams[[paramName]], testParams[[paramName]][1])
expect_error(func(testParams),
info = paste0("Checking for wrong ", paramDesc, " (incorrect value size)"))
}
# Check below min value
if (!is.null(checkMin) && !is.na(checkMin)) {
testParams = params
testParams[[paramName]][1] <- checkMin
expect_error(func(testParams),
info = paste0("Checking for wrong ", paramDesc, " (incorrect value < min)"))
}
# Check under max value
if (!is.null(checkMax) && !is.na(checkMax)) {
testParams = params
testParams[[paramName]][length(testParams[[paramName]])] <- checkMax
expect_error(func(testParams),
info = paste0("Checking for wrong ", paramDesc, " (incorrect value > max)"))
}
}
testParameterErrors(normalCase,
'sample_size',
'Number of enrolled patients',
checkMissing = TRUE,
checkSize = FALSE,
checkMin = 0,
checkMax = 1001)
testParameterErrors(normalCase,
'futility_threshold',
'Futility threshold at IA1',
checkMissing = TRUE,
checkSize = FALSE,
checkMin = -0.001,
checkMax = 0.999)
testParameterErrors(normalCase,
'dropout_rate',
'Patient dropout rate',
checkMissing = FALSE,
checkSize = FALSE,
checkMin = -0.001,
checkMax = 1)
testParameterErrors(normalCase,
'nsims',
'Number of simulations',
checkMissing = FALSE,
checkSize = FALSE,
checkMin = 0,
checkMax = 10001)
testParameterErrors(normalCase,
'alpha',
'One-sided Type I error rate',
checkMissing = FALSE,
checkSize = TRUE,
checkMin = 0.001,
checkMax = 0.5)
testParameterErrors(normalCase,
'control_mean',
'Mean effect in the control arm',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = NA,
checkMax = NA)
testParameterErrors(normalCase,
'treatment_mean',
'Mean effects in the treatment arms',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = NA,
checkMax = NA)
testParameterErrors(normalCase,
'control_sd',
'Standard deviation in the control arm',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = 0,
checkMax = NA)
testParameterErrors(normalCase,
'treatment_sd',
'Standard deviations in the treatment arms',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = 0,
checkMax = NA)
testParameterErrors(normalCase,
'treatment_count',
'Number of selected treatments',
checkMissing = TRUE,
checkWrong = "Not a number",
checkSize = FALSE,
checkMin = 0,
checkMax = length(normalCase$sample_size))
testParameterErrors(normalCase,
'mult_test',
'Multiple testing procedure',
checkMissing = TRUE,
checkWrong = "Wrong value",
checkSize = FALSE,
checkMin = NA,
checkMax = NA)
testParameterErrors(binaryCase,
'control_rate',
'Response rate in the control arm',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = 0,
checkMax = 1)
testParameterErrors(binaryCase,
'treatment_rate',
'Responses rate in the treatment arms',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = 0,
checkMax = 1)
testParameterErrors(binaryCase,
'treatment_rate',
'Responses rate in the treatment arms',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = 0,
checkMax = 1)
testParameterErrors(timeToEventCase,
'control_time',
'Median time in the control arm',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = 0,
checkMax = NA)
testParameterErrors(timeToEventCase,
'treatment_time',
'Median times in the treatment arms',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = 0,
checkMax = NA)
testParameterErrors(timeToEventCase,
'enrollment_period',
'Patient enrollment period',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = 0,
checkMax = NA)
testParameterErrors(timeToEventCase,
'enrollment_parameter',
'Median enrollment time',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = 0,
checkMax = timeToEventCase$enrollment_period)
testParameterErrors(timeToEventCase,
'event_count',
'Target number of events at FA',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = 0,
checkMax = sum(timeToEventCase$sample_size))
})
test_that("Input parameters errors check ADTreatSelReportDoc", {
expect_error(
ADTreatSelReportDoc(""),
info = "Checking for wrong parameter type for report generator"
)
})
medianasoft/MedianaDesigner documentation built on Aug. 28, 2023, 6:33 p.m.
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commonNSim = 50
isTestMultiCore = FALSE
# Normal case parameters
normalCase = list(
# Number of trial arms
narms = 3,
# Sample size
sample_size = c(120, 120, 120),
# Primary endpoint's type
endpoint_type = "Normal",
# Direction of favorable outcome (Higher or Lower)
# Default: Higher
#direction = "Higher",
# Mean and SD in the control arm
control_mean = 0,
control_sd = 1,
# Mean and SD in the treatment arm
treatment_mean = c(0.3, 0.3),
treatment_sd = c(1, 1),
# Information fractions at IA1, IA2, FA
info_frac = c(0.4, 0.6, 1.0),
# Futility threshold for conditional power at IA1
futility_threshold = 0.1,
# Number of selected treatments
treatment_count = 1,
# Multiple testing procedure (Bonferroni, Holm or Hochberg)
mult_test = "Bonferroni",
# Dropout rate at the end of the treatment period
dropout_rate = 0.05,
# One-sided Type I error rate
alpha = 0.025,
# Number of simulations
nsims = commonNSim
)
# Binary case parameters
binaryCase = list(
# Endpoint type
endpoint_type = "Binary",
# Direction of favorable outcome (Higher or Lower)
# Default: Higher
direction = "Higher",
# Number of enrolled patients (control, three treatments)
sample_size = c(150, 150, 150, 150),
# Patient dropout rate
dropout_rate = 0.1,
# Response rate in the control arm
control_rate = 0.1,
# Response rates in the treatment arms
treatment_rate = c(0.25, 0.25, 0.25),
# Information fractions at IA1, IA2, FA
info_frac = c(0.4, 0.6, 1),
# Futility threshold for conditional power at IA1
futility_threshold = 0.15,
# Number of selected treatments
treatment_count = 1,
# Multiple testing procedure (Bonferroni, Holm or Hochberg)
mult_test = "Bonferroni",
# One-sided alpha level
alpha = 0.025,
# Number of simulations
nsims = commonNSim
)
binaryCase2 = list(
# Endpoint type
endpoint_type = "Binary",
# Number of enrolled patients (placebo and four regimens)
sample_size = c(90, 90, 90, 90, 90),
# Response rate in the control arm
control_rate = 0.1,
# Response rates in the regimen arms
treatment_rate = c(0.30, 0.30, 0.35, 0.35),
# Information fractions at Interim analysis 1, Interim analysis 2, Final analysis
info_frac = c(0.2, 0.5, 1),
# Futility threshold for conditional power at Interim analysis 1
futility_threshold = 0.3,
# Patient dropout rate at the end of the 26-week treatment period
dropout_rate = 0.15,
# Number of treatments to be selected at the second interim analysis
treatment_count = 1,
# Multiple testing procedure to be used in the trial
mult_test = "Hochberg",
# One-sided alpha level
alpha = 0.025,
# Number of simulations
nsims = commonNSim
)
# Time-to-event case parameters
timeToEventCase = list(
# Endpoint type
endpoint_type = "Time-to-event",
# Direction of favorable outcome (Higher or Lower)
# Default: Higher
direction = "Higher",
# Number of enrolled patients (control, two treatments)
sample_size = c(180, 180, 180),
# Annual patient dropout rate
dropout_rate = 0.05,
# Median time in the control arm
control_time = 7.5,
# Median times in the treatment arms
treatment_time = c(10.5, 10.5),
# Target event count at FA
event_count = 450,
# Information fractions at IA1, IA2, FA
info_frac = c(0.4, 0.6, 1),
# Futility threshold for conditional power at IA1
futility_threshold = 0.1,
# Number of selected treatments
treatment_count = 1,
# Multiple testing procedure (Bonferroni, Holm or Hochberg)
mult_test = "Bonferroni",
# Enrollment period
enrollment_period = 24,
# Median enrollment time
enrollment_parameter = 18,
# One-sided alpha level
alpha = 0.025,
# Number of simulations
nsims = commonNSim
)
context("ADTreatSel - Success runs")
checkExpectationsForNormalCase = function(results) {
expect_s3_class(results, "ADTreatSelResults")
expect_type( results$sim_results, "double")
expect_length(results$sim_results, 7 * results$parameters$nsims)
sim_summary = results$sim_summary
# print(sim_summary)
expect_type( sim_summary, "list")
expect_equal( sim_summary$ad_power, 0.641, tolerance=0.1)
expect_equal( sim_summary$overall_futility, 0.076, tolerance=0.1)
expect_is( sim_summary$select, "numeric")
expect_length( sim_summary$select, 2)
expect_equal(unname(sim_summary$select[1]), 0.453, tolerance=0.1)
expect_equal(unname(sim_summary$select[2]), 0.453, tolerance=0.1)
expect_is( sim_summary$futility, "numeric")
expect_length( sim_summary$futility, 2)
expect_equal(unname(sim_summary$futility[1]), 0.190, tolerance=0.1)
expect_equal(unname(sim_summary$futility[2]), 0.186, tolerance=0.1)
expect_is( sim_summary$trad_power, "numeric")
expect_length( sim_summary$trad_power, 2)
expect_equal(unname(sim_summary$trad_power[1]), 0.596, tolerance=0.1)
expect_equal(unname(sim_summary$trad_power[2]), 0.586, tolerance=0.1)
}
test_that("Success run ADTreatSel with Normal case (single core)", {
# Success run
results = ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
info_frac = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
# use default
#dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
# use default
#nsims = normalCase$nsims
# Run one with random seek value
random_seed = 49283
)
)
checkExpectationsForNormalCase(results)
# Check for report generation
ADTreatSelReportDoc(results)
})
if (isTestMultiCore) {
test_that("Success run ADTreatSel with Normal case (two cores)", {
# Success run
params = normalCase
params$ncores = 2
results = ADTreatSel(params)
checkExpectationsForNormalCase(results)
})
}
test_that("Success run ADTreatSel with Binary case", {
# Success run
results = ADTreatSel(
list(
endpoint_type = binaryCase$endpoint_type,
sample_size = binaryCase$sample_size,
dropout_rate = binaryCase$dropout_rate,
control_rate = binaryCase$control_rate,
treatment_rate = binaryCase$treatment_rate,
info_frac = binaryCase$info_frac,
futility_threshold = binaryCase$futility_threshold,
treatment_count = binaryCase$treatment_count,
mult_test = binaryCase$mult_test,
# use default
#alpha = binaryCase$alpha,
nsims = binaryCase$nsims
)
)
expect_is(results, "ADTreatSelResults")
expect_type( results$sim_results, "double")
expect_length(results$sim_results, 10 * binaryCase$nsims)
expect_type( results$sim_summary, "list")
expect_true(abs(results$sim_summary$ad_power - 0.8) < 0.2)
expect_true(abs(results$sim_summary$overall_futility - 0.1) < 0.1)
expect_is( results$sim_summary$select, "numeric")
expect_length( results$sim_summary$select, 3)
expect_equivalent(results$sim_summary$select, c(0.35, 0.33, 0.42), tolerance=0.1)
expect_is( results$sim_summary$futility, "numeric")
expect_length( results$sim_summary$futility, 3)
expect_true(abs(results$sim_summary$futility[1] - 0.1) < 0.1)
expect_true(abs(results$sim_summary$futility[2] - 0.1) < 0.1)
expect_true(abs(results$sim_summary$futility[3] - 0.1) < 0.1)
expect_is( results$sim_summary$trad_power, "numeric")
expect_length( results$sim_summary$trad_power, 3)
expect_true(abs(results$sim_summary$trad_power[1] - 0.8) < 0.2)
expect_true(abs(results$sim_summary$trad_power[2] - 0.8) < 0.2)
expect_true(abs(results$sim_summary$trad_power[3] - 0.8) < 0.2)
# Check for report generation
ADTreatSelReportDoc(results)
})
checkExpectationsForBinaryCase2 = function(res) {
expect_s3_class(res, "ADTreatSelResults")
# check sim_results
expect_length(res$sim_results, 13 * res$parameters$nsims)
# check sim_summary
expect_equal(res$sim_summary$ad_power, 0.9175, tolerance=0.1)
expect_equal(res$sim_summary$overall_futility, 0.0179, tolerance=0.1)
expect_equivalent(res$sim_summary$trad_power, c(0.7133, 0.7175, 0.8435, 0.8375), tolerance=0.1)
expect_equivalent(res$sim_summary$select, c(0.1612, 0.1639, 0.3867, 0.3801), tolerance=0.2)
expect_equivalent(res$sim_summary$futility, c(0.2326, 0.2253, 0.1424, 0.1468), tolerance=0.2)
}
test_that("Success run ADTreatSel with Binary case 2 (one core)", {
# Success run
params = binaryCase2
params$sims = 100
# params$ncores = 1
res = ADTreatSel(params)
checkExpectationsForBinaryCase2(res)
})
test_that("Success run ADTreatSel with Binary case 2 (two cores)", {
# Success run
params = binaryCase2
params$sims = 100
params$ncores = 2
res = ADTreatSel(params)
checkExpectationsForBinaryCase2(res)
})
test_that("Success run ADTreatSel with Time-to-event case", {
# Success run
results = ADTreatSel(timeToEventCase)
expect_is(results, "ADTreatSelResults")
expect_type( results$sim_results, "double")
expect_length(results$sim_results, 7 * timeToEventCase$nsims)
expect_type( results$sim_summary, "list")
expect_true(abs(results$sim_summary$ad_power - 0.8) < 0.2)
expect_true(abs(results$sim_summary$overall_futility - 0.1) < 0.1)
expect_is( results$sim_summary$select, "numeric")
expect_length( results$sim_summary$select, 2)
expect_true(abs(results$sim_summary$select[1] - 0.49) < 0.1)
expect_true(abs(results$sim_summary$select[2] - 0.47) < 0.1)
expect_is( results$sim_summary$futility, "numeric")
expect_length( results$sim_summary$futility, 2)
expect_true(abs(results$sim_summary$futility[1] - 0.1) < 0.1)
expect_true(abs(results$sim_summary$futility[2] - 0.1) < 0.1)
expect_is( results$sim_summary$trad_power, "numeric")
expect_length( results$sim_summary$trad_power, 2)
expect_true(abs(results$sim_summary$trad_power[1] - 0.8) < 0.2)
expect_true(abs(results$sim_summary$trad_power[2] - 0.8) < 0.2)
# Check for report generation
ADTreatSelReportDoc(results)
})
test_that("Success run ADTreatSel with Normal case and short sample_size vector", {
# Success run
results = ADTreatSel(
list(
narms = normalCase$narms,
sample_size = c(120, 120), #normalCase$sample_size = c(120, 120, 120)
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = c(0.3), # treatment_mean = c(0.3, 0.3),
treatment_sd = c(1), # treatment_sd = c(1, 1),
info_frac = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
)
expect_is(results, "ADTreatSelResults")
expect_type( results$sim_results, "double")
expect_length(results$sim_results, 4 * normalCase$nsims)
expect_type( results$sim_summary, "list")
expect_true(abs(results$sim_summary$ad_power - 0.5) < 0.3)
expect_true(abs(results$sim_summary$overall_futility - 0.2) < 0.1)
expect_is( results$sim_summary$select, "numeric")
expect_length( results$sim_summary$select, 1)
expect_true(abs(results$sim_summary$select[1] - 0.7) < 0.2)
expect_is( results$sim_summary$futility, "numeric")
expect_length( results$sim_summary$futility, 1)
expect_true(abs(results$sim_summary$futility[1] - 0.2) < 0.1)
expect_is( results$sim_summary$trad_power, "numeric")
expect_length( results$sim_summary$trad_power, 1)
expect_true(abs(results$sim_summary$trad_power[1] - 0.5) < 0.2)
# Check for report generation
ADTreatSelReportDoc(results)
GenerateReport(results, tempfile(fileext = ".docx"))
})
test_that("Success run ADTreatSel with Lower direction", {
# Success run
results = ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
direction = "Lower",
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
info_frac = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
)
expect_is(results, "ADTreatSelResults")
expect_type( results$sim_results, "double")
expect_length(results$sim_results, 7 * normalCase$nsims)
expect_type( results$sim_summary, "list")
expect_is( results$sim_summary$select, "numeric")
expect_is( results$sim_summary$futility, "numeric")
expect_is( results$sim_summary$trad_power, "numeric")
# Check for report generation
ADTreatSelReportDoc(results)
})
context("ADTreatSel - Error checks")
test_that("Input parameters errors check ADTreatSel", {
# Errors check
expect_error(
ADTreatSel(
c("Not a list")
),
info = "Checking for wrong parameters collection type"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
# missing
#endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
info_frac = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for missing endpoint type"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
# wrong
endpoint_type = "SomeType", #normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
info_frac = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
dropout_rate = normalCase$dropout_rate,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for missing endpoint type"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
endpoint_type = normalCase$endpoint_type,
# wrong
direction = "Wrong",
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
info_frac = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for wrong direction"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
# missing
#info_frac = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for missing information fractions at IA1, IA2, FA"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
# wrong (IA1 >= IA2)
info_frac = c(0.8, 0.6, 1.0), # normalCase$info_frac == c(0.4, 0.6, 1.0),
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for wrong information fraction (IA1 must be < IA2)"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
# wrong (IA2 >= FA)
info_frac = c(0.4, 1.0, 0.9), # normalCase$info_frac == c(0.4, 0.6, 1.0),
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for wrong information fraction (IA2 must be < FA)"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
# wrong (FA != 1)
info_frac = c(0.4, 0.6, 0.9), # normalCase$info_frac == c(0.4, 0.6, 1.0),
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for wrong information fraction (FA must be 1)"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
# wrong
info_frac = c(0.4, 0.6), # c(0.4, 0.6, 1.0) = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for wrong information fractions at IA1, IA2, FA (incorrect length)"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
# wrong
info_frac = c(0, 0.6, 1.0), # c(0.4, 0.6, 1.0) = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for wrong information fractions at IA1, IA2, FA (value <= 0)"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
# wrong
info_frac = c(0.4, 0.6, 1.1), # c(0.4, 0.6, 1.0) = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for wrong information fractions at IA1, IA2, FA (value > 1)"
)
expect_error(
ADTreatSel(
list(
narms = normalCase$narms,
sample_size = normalCase$sample_size,
endpoint_type = normalCase$endpoint_type,
control_mean = normalCase$control_mean,
control_sd = normalCase$control_sd,
treatment_mean = normalCase$treatment_mean,
treatment_sd = normalCase$treatment_sd,
# wrong
info_frac = c(0.4, 0.6, "1.0"), # c(0.4, 0.6, 1.0) = normalCase$info_frac,
futility_threshold = normalCase$futility_threshold,
treatment_count = normalCase$treatment_count,
mult_test = normalCase$mult_test,
dropout_rate = normalCase$dropout_rate,
alpha = normalCase$alpha,
nsims = normalCase$nsims
)
),
info = "Checking for wrong information fractions at IA1, IA2, FA (value not a number)"
)
# Universal parameter check func
testParameterErrors = function(params, paramName, paramDesc,
checkMissing = TRUE, checkWrong = NA, checkSize = TRUE, checkMin = NA, checkMax = NA) {
func = ADTreatSel
paramDesc = paste0(paramDesc, " (", paramName, ")")
if (!is.null(params$endpoint_type))
paramDesc = paste0(params$endpoint_type, ": ", paramDesc)
# Missing
if (checkMissing) {
testParams = params
testParams[paramName] <- NULL
expect_error(func(testParams),
info = paste0("Checking for missing ", paramDesc))
}
# Wrong
if (!is.null(checkWrong) && !is.na(checkWrong)) {
testParams = params
testParams[paramName] <- checkWrong
expect_error(func(testParams),
info = paste0("Checking for wrong ", paramDesc))
}
# Check size
if (checkSize) {
testParams = params
testParams[[paramName]] <- append(testParams[[paramName]], testParams[[paramName]][1])
expect_error(func(testParams),
info = paste0("Checking for wrong ", paramDesc, " (incorrect value size)"))
}
# Check below min value
if (!is.null(checkMin) && !is.na(checkMin)) {
testParams = params
testParams[[paramName]][1] <- checkMin
expect_error(func(testParams),
info = paste0("Checking for wrong ", paramDesc, " (incorrect value < min)"))
}
# Check under max value
if (!is.null(checkMax) && !is.na(checkMax)) {
testParams = params
testParams[[paramName]][length(testParams[[paramName]])] <- checkMax
expect_error(func(testParams),
info = paste0("Checking for wrong ", paramDesc, " (incorrect value > max)"))
}
}
testParameterErrors(normalCase,
'sample_size',
'Number of enrolled patients',
checkMissing = TRUE,
checkSize = FALSE,
checkMin = 0,
checkMax = 1001)
testParameterErrors(normalCase,
'futility_threshold',
'Futility threshold at IA1',
checkMissing = TRUE,
checkSize = FALSE,
checkMin = -0.001,
checkMax = 0.999)
testParameterErrors(normalCase,
'dropout_rate',
'Patient dropout rate',
checkMissing = FALSE,
checkSize = FALSE,
checkMin = -0.001,
checkMax = 1)
testParameterErrors(normalCase,
'nsims',
'Number of simulations',
checkMissing = FALSE,
checkSize = FALSE,
checkMin = 0,
checkMax = 10001)
testParameterErrors(normalCase,
'alpha',
'One-sided Type I error rate',
checkMissing = FALSE,
checkSize = TRUE,
checkMin = 0.001,
checkMax = 0.5)
testParameterErrors(normalCase,
'control_mean',
'Mean effect in the control arm',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = NA,
checkMax = NA)
testParameterErrors(normalCase,
'treatment_mean',
'Mean effects in the treatment arms',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = NA,
checkMax = NA)
testParameterErrors(normalCase,
'control_sd',
'Standard deviation in the control arm',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = 0,
checkMax = NA)
testParameterErrors(normalCase,
'treatment_sd',
'Standard deviations in the treatment arms',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = 0,
checkMax = NA)
testParameterErrors(normalCase,
'treatment_count',
'Number of selected treatments',
checkMissing = TRUE,
checkWrong = "Not a number",
checkSize = FALSE,
checkMin = 0,
checkMax = length(normalCase$sample_size))
testParameterErrors(normalCase,
'mult_test',
'Multiple testing procedure',
checkMissing = TRUE,
checkWrong = "Wrong value",
checkSize = FALSE,
checkMin = NA,
checkMax = NA)
testParameterErrors(binaryCase,
'control_rate',
'Response rate in the control arm',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = 0,
checkMax = 1)
testParameterErrors(binaryCase,
'treatment_rate',
'Responses rate in the treatment arms',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = 0,
checkMax = 1)
testParameterErrors(binaryCase,
'treatment_rate',
'Responses rate in the treatment arms',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = 0,
checkMax = 1)
testParameterErrors(timeToEventCase,
'control_time',
'Median time in the control arm',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = 0,
checkMax = NA)
testParameterErrors(timeToEventCase,
'treatment_time',
'Median times in the treatment arms',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = 0,
checkMax = NA)
testParameterErrors(timeToEventCase,
'enrollment_period',
'Patient enrollment period',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = 0,
checkMax = NA)
testParameterErrors(timeToEventCase,
'enrollment_parameter',
'Median enrollment time',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = 0,
checkMax = timeToEventCase$enrollment_period)
testParameterErrors(timeToEventCase,
'event_count',
'Target number of events at FA',
checkMissing = TRUE,
checkSize = TRUE,
checkMin = 0,
checkMax = sum(timeToEventCase$sample_size))
})
test_that("Input parameters errors check ADTreatSelReportDoc", {
expect_error(
ADTreatSelReportDoc(""),
info = "Checking for wrong parameter type for report generator"
)
})
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