### Test code ###

library(CohortMethod)

cdmDatabaseSchema <- "CDM_IBM_MDCD_V1153.dbo"

resultsDatabaseSchema <- "Scratch.dbo"

cdmVersion <- "5"

connectionDetails <- DatabaseConnector::createConnectionDetails(dbms = "pdw",

server = Sys.getenv("PDW_SERVER"),

user = NULL,

password = NULL,

port = Sys.getenv("PDW_PORT"))

checkCmInstallation(connectionDetails)

covariateSettings <- createCovariateSettings(useDemographicsGender = TRUE,

useDemographicsAgeGroup = TRUE)

cohortMethodData <- getDbCohortMethodData(connectionDetails = connectionDetails,

cdmDatabaseSchema = cdmDatabaseSchema,

exposureTable = "drug_era",

outcomeTable = "condition_era",

targetId = 755695,

comparatorId = 739138,

outcomeIds = 194133,

cdmVersion = cdmVersion,

washoutPeriod = 183,

firstExposureOnly = TRUE,

removeDuplicateSubjects = "remove all",

restrictToCommonPeriod = TRUE,

maxCohortSize = 100000,

covariateSettings = covariateSettings)

saveCohortMethodData(cohortMethodData, "s:/temp/cmData2")

cohortMethodData <- loadCohortMethodData("s:/temp/cmData2")

studyPop <- createStudyPopulation(cohortMethodData,

removeSubjectsWithPriorOutcome = TRUE,

restrictToCommonPeriod = TRUE,

outcomeId = 194133)

ps <- createPs(cohortMethodData,

studyPop,

maxCohortSizeForFitting = 10000,

prior = createPrior("laplace", variance = 0.01))

attr(ps, "metaData")

plotPs(ps)

strata <- matchOnPs(ps)

plotPs(strata, ps)

fitOutcomeModel(population = strata,

cohortMethodData = cohortMethodData,

modelType = "cox",

stratified = TRUE,

prior = createPrior("laplace", 0.01))

targetComparatorOutcomes1 <- createTargetComparatorOutcomes(targetId = 755695,

comparatorId = 739138,

outcomeIds = c(194133, 123))

targetComparatorOutcomesList <- list(targetComparatorOutcomes1)

saveTargetComparatorOutcomesList(targetComparatorOutcomesList,

"s:/temp/targetComparatorOutcomesList.json.txt")

covariateSettings <- createCovariateSettings()

getDbCmDataArgs <- createGetDbCohortMethodDataArgs(excludeDrugsFromCovariates = TRUE,

covariateSettings = covariateSettings)

createPsArgs <- createCreatePsArgs() # Using only defaults

matchOnPsArgs <- createMatchOnPsArgs(maxRatio = 1)

fitOutcomeModelArgs1 <- createFitOutcomeModelArgs(riskWindowStart = 0,

riskWindowEnd = 365,

addExposureDaysToEnd = FALSE,

modelType = "cox",

stratifiedCox = TRUE,

useCovariates = TRUE)

cmAnalysis1 <- createCmAnalysis(analysisId = 1,

getDbCohortMethodDataArgs = getDbCmDataArgs,

createPs = TRUE,

createPsArgs = createPsArgs,

matchOnPs = TRUE,

matchOnPsArgs = matchOnPsArgs,

fitOutcomeModel = TRUE,

fitOutcomeModelArgs = fitOutcomeModelArgs1)

fitOutcomeModelArgs2 <- createFitOutcomeModelArgs(riskWindowStart = 0,

riskWindowEnd = 365,

addExposureDaysToEnd = FALSE,

modelType = "cox",

stratifiedCox = TRUE,

useCovariates = FALSE)

cmAnalysis2 <- createCmAnalysis(analysisId = 2,

getDbCohortMethodDataArgs = getDbCmDataArgs,

createPs = TRUE,

createPsArgs = createPsArgs,

matchOnPs = TRUE,

matchOnPsArgs = matchOnPsArgs,

fitOutcomeModel = TRUE,

fitOutcomeModelArgs = fitOutcomeModelArgs2)

cmAnalysis2 <- createCmAnalysis(analysisId = 2,

getDbCohortMethodDataArgs = getDbCmDataArgs,

fitOutcomeModel = TRUE,

fitOutcomeModelArgs = fitOutcomeModelArgs2)

cmAnalysisList <- list(cmAnalysis1, cmAnalysis2)

saveCmAnalysisList(cmAnalysisList, "s:/temp/cohortMethodAnalysisList.json.txt")

cmAnalysisList <- loadCmAnalysisList("s:/temp/cohortMethodAnalysisList.json.txt")

targetComparatorOutcomesList <- loadTargetComparatorOutcomesList("s:/temp/targetComparatorOutcomesList.json.txt")

cmAnalysisList <- loadCmAnalysisList("s:/temp/cohortMethodAnalysisList.json.txt")

targetComparatorOutcomesList <- loadTargetComparatorOutcomesList("s:/temp/targetComparatorOutcomesList.json.txt")

# Settings for running SQL against JnJ Sql Server:

pw <- NULL

dbms <- "sql server"

user <- NULL

server <- "RNDUSRDHIT09"

cdmDatabaseSchema <- "CDM_TRUVEN_CCAE_6k.dbo"

# cdmSchema <- 'CDM_Truven_MDCR'

port <- NULL

# Part one: loading the data:

connectionDetails <- DatabaseConnector::createConnectionDetails(dbms = dbms,

server = server,

user = user,

password = pw,

schema = cdmDatabaseSchema,

port = port)

ref <- runCmAnalyses(connectionDetails = connectionDetails,

cdmDatabaseSchema = cdmDatabaseSchema,

outputFolder = "s:/temp/cmOutput",

cmAnalysisList = cmAnalysisList,

targetComparatorOutcomesList = targetComparatorOutcomesList,

underSampleComparatorToTreatedRatio = 1,

getDbCohortMethodDataThreads = 2,

createPsThreads = 1,

fitOutcomeModelThreads = 1)

# Test KM plot ------------------------------------------------------------

library(CohortMethod)

data(cohortMethodDataSimulationProfile)

sampleSize <- 100000

cohortMethodData <- simulateCohortMethodData(cohortMethodDataSimulationProfile, n = sampleSize)

studyPop <- createStudyPopulation(cohortMethodData = cohortMethodData,

addExposureDaysToEnd = TRUE,

outcomeId = 194133)

plotKaplanMeier(studyPop, fileName = "s:/temp/plot.png")

# Test power function -----------------------------------------------------

result <- readRDS("s:/temp/cohortMethodVignette2/outcomeModelReference.rds")

result <- result[result$studyPopFile != "", ]

for (i in 1:nrow(result)) {

if (result$strataFile[i] == "") {

population <- readRDS(result$studyPopFile[i])

} else {

population <- readRDS(result$strataFile[i])

}

om <- readRDS(result$outcomeModelFile[i])

writeLines(paste(computeMdrr(population)$se, om$outcomeModelTreatmentEstimate$seLogRr))

}

# Profile variable-ratio matching

library(CohortMethod)

for (i in 1:20) {

rowId <- 1:1e 06

treatment <- rep(0:1, 2.5e 04)

set.seed(123)

propensityScore <- runif(length(rowId), 0, 1)

data <-

data.frame(rowId = rowId,

treatment = treatment,

propensityScore = propensityScore)

system.time(result <- matchOnPs(data, caliper = 0, maxRatio = 100))

}

# Unit test

library(CohortMethod)

rowId <- 1:1e 06

treatment <- rep(0:1, length(rowId) / 2)

set.seed(123)

propensityScore <- runif(length(rowId), 0, 1)

data <-

data.frame(rowId = rowId,

treatment = treatment,

propensityScore = propensityScore)

system.time(result <- matchOnPs(data, caliper = 0, maxRatio = 100))

# unitTestResult <- result

# save(unitTestResult, file = "unitTest.Rda")

load("unitTest.Rda")