tests/testthat/test-ADRand.r
In medianasoft/MedianaDesigner: Power and Sample Size Calculations for Clinical Trials
commonNSim = 50
isTestMultiCore = FALSE
#####################################
# List of all parameters.
normalCase <- list(
# --[ Endpoint Parameters ]--------------------------------------------------
# Endpoint distribution type (Normal)
endpoint_type = "Normal",
# Direction of favorable outcome (Lower, Higher)
direction = "Higher",
# --[ Design Assumptions ]---------------------------------------------------
# Dose levels in the trial (with 0 corresponding to the placebo arm)
dose_levels = c(0, 150, 300, 600),
# Total number of enrolled patients in each trial stage
stage_sample_size = c(100, 100, 100, 100),
# Length of the patient enrollment period
enrollment_period = 52,
# Median enrollment time, i.e., the time point by which
# 50% of the patients will be enrolled into the trial
enrollment_parameter = 36,
# Length of the treatment period
treatment_period = 6,
# Patient dropout rate
dropout_rate = 0.1,
#--[ Treatment Assumptions ]-------------------------------------------------
# Mean and SD in the control arm
control_mean = 10,
control_sd = 25,
# Mean and SD in the treatment arms
treatment_mean = c(15, 20, 22),
treatment_sd = c(25, 25, 25),
# Fixed randomization ratio in the placebo arm
ratio_placebo = 0.25,
# Balance parameter for adaptive randomization
balance = 1,
# Non-linear parameters of the candidate dose-response models used
# in the MCPMod method
exponential_model_parameter = 600,
emax_model_parameter = 600,
logistic_model_parameters = c(200, 200),
# --[ General Parameters ]---------------------------------------------------
# Clinically relevant improvement over placebo
delta = 10,
# One-sided Type I error rate
alpha = 0.025,
# Number of simulations
nsims = commonNSim
)
#####################################
context("ADRand - Success runs")
checkExpectationsForNormalCase = function(res) {
expect_s3_class(res, "ADRandResults")
expect_length(res, 2)
expect_length(res$sim_results, 5)
# Calculate summary
parameters = res$parameters
simulations = res$sim_results
# print(simulations$n)
# - ComparisonOfTraditionalAndAdaptiveDesigns -----------------------------------------
rowMax = function(x) {
row_max = rep(0, nrow(x))
for (i in 1:nrow(x)) row_max[i] = max(x[i, ])
return(row_max)
}
traditional = mean(rowMax(simulations$traditional) >= simulations$mcpmod_value)
adaptive = mean(rowMax(simulations$adaptive) >= simulations$mcpmod_value)
expect_equal(traditional, 0.9, tolerance=0.1)
expect_equal(adaptive, 0.9, tolerance=0.1)
# -------------------------------------------------------------------------------------
# - SampleSizeByTrialArm --------------------------------------------------------------
col3 = NULL
n_doses = length(parameters$dose_levels)
for (i in 1:n_doses) {
col3 = c(col3, round(summary(simulations$n[, i])[c(1, 3, 4, 6)], 1))
}
col3 = unname(col3)
expect_equal(
col3,
# Min. Median Mean Max. Min. Median Mean Max. Min. Median Mean Max. Min. Median Mean Max.
c(89.0, 90.0, 90.2, 92.0, 79.0, 85.5, 87.2, 144.0, 64.0, 90.0, 89.8, 96.0, 63.0, 94.0, 93.6, 102.0),
tolerance=10
)
# -------------------------------------------------------------------------------------
}
test_that("Success run ADRand with Normal case (single core)", {
parameters = normalCase
# Run once with random_seed parameter
parameters$random_seed = 49283
# Skip chart generation in tests
parameters$withoutCharts = TRUE
# Run simulations
results = ADRand(parameters)
checkExpectationsForNormalCase(results)
expect_length(results$parameters, length(normalCase)+12)
# Create a simulation report
temp_file = tempfile("Simulation report.docx", fileext=".docx")
GenerateReport(results, temp_file)
expect_true(file.exists(temp_file))
expect_true(file.size(temp_file) > 15000)
# Check for report generation
ADRandReportDoc(results)
GenerateReport(results, tempfile(fileext = ".docx"))
})
if (isTestMultiCore) {
test_that("Success run ADRand with Normal case (two cores)", {
parameters = normalCase
parameters$ncores = 2
# Skip chart generation in tests
parameters$withoutCharts = TRUE
# Run simulations
results = ADRand(parameters)
checkExpectationsForNormalCase(results)
})
}
test_that("Success run ADRand with Normal case with insignificant changes", {
# Remove parameters that accepts default value
changedNormalCase <- normalCase
changedNormalCase['direction'] = NULL
changedNormalCase['dropout_rate'] = NULL
changedNormalCase['alpha'] = NULL
changedNormalCase['balance'] = NULL
changedNormalCase['nsims'] = 25
# Run simulations
results = ADRand(changedNormalCase)
expect_is(results, "ADRandResults")
expect_equal(length(results), 2)
expect_equal(length(results$sim_results), 5)
})
test_that("Success run ADRand with Normal case with changed direction", {
# Remove parameters that accept default value
changedNormalCase <- normalCase
changedNormalCase['direction'] = "Lower"
changedNormalCase['delta'] = -10
changedNormalCase['nsims'] = 25
# Run simulations
results = ADRand(changedNormalCase)
expect_is(results, "ADRandResults")
expect_equal(length(results), 2)
expect_equal(length(results$sim_results), 5)
# TODO: Check result
})
# TODO: More success runs
context("ADRand - Error checks")
test_that("Input parameters errors check ADRand", {
# Errors check
expect_error(
ADRand(
c("Not a list")
),
info = "Checking for wrong parameters collection type"
)
# Universal parameter check func
testParameterErrors = function(params, paramName, paramDesc,
checkMissing = TRUE, checkWrong = NA, checkSize = TRUE, checkMin = NA, checkMax = NA) {
func = ADRand
paramDesc = paste0(paramDesc, " (", paramName, ")")
if (!is.null(params$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,
'endpoint_type',
'Endpoint Type',
checkMissing = TRUE,
checkWrong = "wrong",
checkSize = FALSE,
checkMin = NA,
checkMax = NA)
# direction = "Higher",
testParameterErrors(normalCase,
'direction',
'Direction',
checkMissing = FALSE,
checkWrong = "Back",
checkSize = FALSE,
checkMin = NA,
checkMax = NA)
# dose_levels = c(0, 150, 300, 600),
testParameterErrors(normalCase,
'dose_levels',
'Dose levels',
checkMissing = TRUE,
checkWrong = "String",
checkSize = FALSE,
checkMin = -1,
checkMax = 1001)
# stage_sample_size = c(100, 100, 100, 100),
testParameterErrors(normalCase,
'stage_sample_size',
'Stage sample size',
checkMissing = TRUE,
checkWrong = FALSE,
checkSize = FALSE,
checkMin = 0,
checkMax = NA)
# enrollment_period = 52,
testParameterErrors(normalCase,
'enrollment_period',
'Enrollment period',
checkMissing = TRUE,
checkWrong = "String",
checkSize = FALSE,
checkMin = 0,
checkMax = NA)
# enrollment_parameter = 36,
testParameterErrors(normalCase,
'enrollment_parameter',
'Enrollment Parameter',
checkMissing = TRUE,
checkWrong = "String",
checkSize = FALSE,
checkMin = 0,
checkMax = normalCase$enrollment_period)
# treatment_period = 6,
testParameterErrors(normalCase,
'treatment_period',
'Treatment Period',
checkMissing = TRUE,
checkWrong = "String",
checkSize = FALSE,
checkMin = 0,
checkMax = NA)
# dropout_rate = 0.1,
testParameterErrors(normalCase,
'dropout_rate',
'Dropout Rate',
checkMissing = FALSE, # default = 0
checkWrong = "String",
checkSize = FALSE,
checkMin = -0.01,
checkMax = 1)
# control_mean = 10,
testParameterErrors(normalCase,
'control_mean',
'Control Mean',
checkMissing = TRUE,
checkWrong = "String",
checkSize = FALSE,
checkMin = NA,
checkMax = NA)
# control_sd = 25,
testParameterErrors(normalCase,
'control_sd',
'Control SD',
checkMissing = TRUE,
checkWrong = "String",
checkSize = FALSE,
checkMin = 0,
checkMax = NA)
# treatment_mean = c(15, 20, 22),
testParameterErrors(normalCase,
'treatment_mean',
'Treatment Mean',
checkMissing = TRUE,
checkWrong = "String",
checkSize = TRUE,
checkMin = NA,
checkMax = NA)
# treatment_sd = c(25, 25, 25),
testParameterErrors(normalCase,
'treatment_sd',
'Treatment SD',
checkMissing = TRUE,
checkWrong = "String",
checkSize = TRUE,
checkMin = 0,
checkMax = NA)
# ratio_placebo = 0.25,
testParameterErrors(normalCase,
'ratio_placebo',
'Ratio Placebo',
checkMissing = TRUE,
checkWrong = "String",
checkSize = FALSE,
checkMin = 0,
checkMax = 1)
# exponential_model_parameter = 600,
testParameterErrors(normalCase,
'exponential_model_parameter',
'Exponential model parameter',
checkMissing = TRUE,
checkWrong = "String",
checkSize = FALSE,
checkMin = 0,
checkMax = NA)
# emax_model_parameter = 600,
testParameterErrors(normalCase,
'emax_model_parameter',
'Emax model parameter',
checkMissing = TRUE,
checkWrong = "String",
checkSize = FALSE,
checkMin = 0,
checkMax = NA)
# logistic_model_parameters = c(200, 200),
testParameterErrors(normalCase,
'logistic_model_parameters',
'Logistic model parameters',
checkMissing = TRUE,
checkWrong = "String",
checkSize = TRUE,
checkMin = 0,
checkMax = NA)
# delta = 10,
testParameterErrors(normalCase,
'delta',
'Delta',
checkMissing = TRUE,
checkWrong = "String",
checkSize = FALSE,
checkMin = -0.01,
checkMax = NA)
# alpha = 0.025,
testParameterErrors(normalCase,
'alpha',
'Alpha',
checkMissing = FALSE, # default = 0.025
checkWrong = "String",
checkSize = FALSE,
checkMin = 0.001,
checkMax = 0.5)
# nsims = 100
testParameterErrors(normalCase,
'nsims',
'Number of simulations',
checkMissing = FALSE, # default = 1000
checkWrong = 99.5,
checkSize = FALSE,
checkMin = 0,
checkMax = 10001)
})
test_that("Input parameters errors check ADRandReportDoc", {
expect_error(
ADRandReportDoc(""),
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
#####################################
# List of all parameters.
normalCase <- list(
# --[ Endpoint Parameters ]--------------------------------------------------
# Endpoint distribution type (Normal)
endpoint_type = "Normal",
# Direction of favorable outcome (Lower, Higher)
direction = "Higher",
# --[ Design Assumptions ]---------------------------------------------------
# Dose levels in the trial (with 0 corresponding to the placebo arm)
dose_levels = c(0, 150, 300, 600),
# Total number of enrolled patients in each trial stage
stage_sample_size = c(100, 100, 100, 100),
# Length of the patient enrollment period
enrollment_period = 52,
# Median enrollment time, i.e., the time point by which
# 50% of the patients will be enrolled into the trial
enrollment_parameter = 36,
# Length of the treatment period
treatment_period = 6,
# Patient dropout rate
dropout_rate = 0.1,
#--[ Treatment Assumptions ]-------------------------------------------------
# Mean and SD in the control arm
control_mean = 10,
control_sd = 25,
# Mean and SD in the treatment arms
treatment_mean = c(15, 20, 22),
treatment_sd = c(25, 25, 25),
# Fixed randomization ratio in the placebo arm
ratio_placebo = 0.25,
# Balance parameter for adaptive randomization
balance = 1,
# Non-linear parameters of the candidate dose-response models used
# in the MCPMod method
exponential_model_parameter = 600,
emax_model_parameter = 600,
logistic_model_parameters = c(200, 200),
# --[ General Parameters ]---------------------------------------------------
# Clinically relevant improvement over placebo
delta = 10,
# One-sided Type I error rate
alpha = 0.025,
# Number of simulations
nsims = commonNSim
)
#####################################
context("ADRand - Success runs")
checkExpectationsForNormalCase = function(res) {
expect_s3_class(res, "ADRandResults")
expect_length(res, 2)
expect_length(res$sim_results, 5)
# Calculate summary
parameters = res$parameters
simulations = res$sim_results
# print(simulations$n)
# - ComparisonOfTraditionalAndAdaptiveDesigns -----------------------------------------
rowMax = function(x) {
row_max = rep(0, nrow(x))
for (i in 1:nrow(x)) row_max[i] = max(x[i, ])
return(row_max)
}
traditional = mean(rowMax(simulations$traditional) >= simulations$mcpmod_value)
adaptive = mean(rowMax(simulations$adaptive) >= simulations$mcpmod_value)
expect_equal(traditional, 0.9, tolerance=0.1)
expect_equal(adaptive, 0.9, tolerance=0.1)
# -------------------------------------------------------------------------------------
# - SampleSizeByTrialArm --------------------------------------------------------------
col3 = NULL
n_doses = length(parameters$dose_levels)
for (i in 1:n_doses) {
col3 = c(col3, round(summary(simulations$n[, i])[c(1, 3, 4, 6)], 1))
}
col3 = unname(col3)
expect_equal(
col3,
# Min. Median Mean Max. Min. Median Mean Max. Min. Median Mean Max. Min. Median Mean Max.
c(89.0, 90.0, 90.2, 92.0, 79.0, 85.5, 87.2, 144.0, 64.0, 90.0, 89.8, 96.0, 63.0, 94.0, 93.6, 102.0),
tolerance=10
)
# -------------------------------------------------------------------------------------
}
test_that("Success run ADRand with Normal case (single core)", {
parameters = normalCase
# Run once with random_seed parameter
parameters$random_seed = 49283
# Skip chart generation in tests
parameters$withoutCharts = TRUE
# Run simulations
results = ADRand(parameters)
checkExpectationsForNormalCase(results)
expect_length(results$parameters, length(normalCase)+12)
# Create a simulation report
temp_file = tempfile("Simulation report.docx", fileext=".docx")
GenerateReport(results, temp_file)
expect_true(file.exists(temp_file))
expect_true(file.size(temp_file) > 15000)
# Check for report generation
ADRandReportDoc(results)
GenerateReport(results, tempfile(fileext = ".docx"))
})
if (isTestMultiCore) {
test_that("Success run ADRand with Normal case (two cores)", {
parameters = normalCase
parameters$ncores = 2
# Skip chart generation in tests
parameters$withoutCharts = TRUE
# Run simulations
results = ADRand(parameters)
checkExpectationsForNormalCase(results)
})
}
test_that("Success run ADRand with Normal case with insignificant changes", {
# Remove parameters that accepts default value
changedNormalCase <- normalCase
changedNormalCase['direction'] = NULL
changedNormalCase['dropout_rate'] = NULL
changedNormalCase['alpha'] = NULL
changedNormalCase['balance'] = NULL
changedNormalCase['nsims'] = 25
# Run simulations
results = ADRand(changedNormalCase)
expect_is(results, "ADRandResults")
expect_equal(length(results), 2)
expect_equal(length(results$sim_results), 5)
})
test_that("Success run ADRand with Normal case with changed direction", {
# Remove parameters that accept default value
changedNormalCase <- normalCase
changedNormalCase['direction'] = "Lower"
changedNormalCase['delta'] = -10
changedNormalCase['nsims'] = 25
# Run simulations
results = ADRand(changedNormalCase)
expect_is(results, "ADRandResults")
expect_equal(length(results), 2)
expect_equal(length(results$sim_results), 5)
# TODO: Check result
})
# TODO: More success runs
context("ADRand - Error checks")
test_that("Input parameters errors check ADRand", {
# Errors check
expect_error(
ADRand(
c("Not a list")
),
info = "Checking for wrong parameters collection type"
)
# Universal parameter check func
testParameterErrors = function(params, paramName, paramDesc,
checkMissing = TRUE, checkWrong = NA, checkSize = TRUE, checkMin = NA, checkMax = NA) {
func = ADRand
paramDesc = paste0(paramDesc, " (", paramName, ")")
if (!is.null(params$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,
'endpoint_type',
'Endpoint Type',
checkMissing = TRUE,
checkWrong = "wrong",
checkSize = FALSE,
checkMin = NA,
checkMax = NA)
# direction = "Higher",
testParameterErrors(normalCase,
'direction',
'Direction',
checkMissing = FALSE,
checkWrong = "Back",
checkSize = FALSE,
checkMin = NA,
checkMax = NA)
# dose_levels = c(0, 150, 300, 600),
testParameterErrors(normalCase,
'dose_levels',
'Dose levels',
checkMissing = TRUE,
checkWrong = "String",
checkSize = FALSE,
checkMin = -1,
checkMax = 1001)
# stage_sample_size = c(100, 100, 100, 100),
testParameterErrors(normalCase,
'stage_sample_size',
'Stage sample size',
checkMissing = TRUE,
checkWrong = FALSE,
checkSize = FALSE,
checkMin = 0,
checkMax = NA)
# enrollment_period = 52,
testParameterErrors(normalCase,
'enrollment_period',
'Enrollment period',
checkMissing = TRUE,
checkWrong = "String",
checkSize = FALSE,
checkMin = 0,
checkMax = NA)
# enrollment_parameter = 36,
testParameterErrors(normalCase,
'enrollment_parameter',
'Enrollment Parameter',
checkMissing = TRUE,
checkWrong = "String",
checkSize = FALSE,
checkMin = 0,
checkMax = normalCase$enrollment_period)
# treatment_period = 6,
testParameterErrors(normalCase,
'treatment_period',
'Treatment Period',
checkMissing = TRUE,
checkWrong = "String",
checkSize = FALSE,
checkMin = 0,
checkMax = NA)
# dropout_rate = 0.1,
testParameterErrors(normalCase,
'dropout_rate',
'Dropout Rate',
checkMissing = FALSE, # default = 0
checkWrong = "String",
checkSize = FALSE,
checkMin = -0.01,
checkMax = 1)
# control_mean = 10,
testParameterErrors(normalCase,
'control_mean',
'Control Mean',
checkMissing = TRUE,
checkWrong = "String",
checkSize = FALSE,
checkMin = NA,
checkMax = NA)
# control_sd = 25,
testParameterErrors(normalCase,
'control_sd',
'Control SD',
checkMissing = TRUE,
checkWrong = "String",
checkSize = FALSE,
checkMin = 0,
checkMax = NA)
# treatment_mean = c(15, 20, 22),
testParameterErrors(normalCase,
'treatment_mean',
'Treatment Mean',
checkMissing = TRUE,
checkWrong = "String",
checkSize = TRUE,
checkMin = NA,
checkMax = NA)
# treatment_sd = c(25, 25, 25),
testParameterErrors(normalCase,
'treatment_sd',
'Treatment SD',
checkMissing = TRUE,
checkWrong = "String",
checkSize = TRUE,
checkMin = 0,
checkMax = NA)
# ratio_placebo = 0.25,
testParameterErrors(normalCase,
'ratio_placebo',
'Ratio Placebo',
checkMissing = TRUE,
checkWrong = "String",
checkSize = FALSE,
checkMin = 0,
checkMax = 1)
# exponential_model_parameter = 600,
testParameterErrors(normalCase,
'exponential_model_parameter',
'Exponential model parameter',
checkMissing = TRUE,
checkWrong = "String",
checkSize = FALSE,
checkMin = 0,
checkMax = NA)
# emax_model_parameter = 600,
testParameterErrors(normalCase,
'emax_model_parameter',
'Emax model parameter',
checkMissing = TRUE,
checkWrong = "String",
checkSize = FALSE,
checkMin = 0,
checkMax = NA)
# logistic_model_parameters = c(200, 200),
testParameterErrors(normalCase,
'logistic_model_parameters',
'Logistic model parameters',
checkMissing = TRUE,
checkWrong = "String",
checkSize = TRUE,
checkMin = 0,
checkMax = NA)
# delta = 10,
testParameterErrors(normalCase,
'delta',
'Delta',
checkMissing = TRUE,
checkWrong = "String",
checkSize = FALSE,
checkMin = -0.01,
checkMax = NA)
# alpha = 0.025,
testParameterErrors(normalCase,
'alpha',
'Alpha',
checkMissing = FALSE, # default = 0.025
checkWrong = "String",
checkSize = FALSE,
checkMin = 0.001,
checkMax = 0.5)
# nsims = 100
testParameterErrors(normalCase,
'nsims',
'Number of simulations',
checkMissing = FALSE, # default = 1000
checkWrong = 99.5,
checkSize = FALSE,
checkMin = 0,
checkMax = 10001)
})
test_that("Input parameters errors check ADRandReportDoc", {
expect_error(
ADRandReportDoc(""),
info = "Checking for wrong parameter type for report generator"
)
})
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