R/additionalTable1.R
In chandryou/TicagrelorVsClopidogrel: A Package Skeleton for Comparative Effectiveness Studies
Defines functions
createTable1
setTableSpecification
mapCovariates
comparativeCharacterization
additionalResult
Documented in
additionalResult
# Copyright 2020 Observational Health Data Sciences and Informatics
#
# This file is part of TicagrelorVsClopidogrel
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#' Generate result for revision
#'
#' @details
#' Generate result for revision
#'
#' The \code{createCohorts}, \code{synthesizePositiveControls}, \code{runAnalyses}, and \code{runDiagnostics} arguments
#' are intended to be used to run parts of the full study at a time, but none of the parts are considerd to be optional.
#'
#' @param connectionDetails An object of type \code{connectionDetails} as created using the
#' \code{\link[DatabaseConnector]{createConnectionDetails}} function in the
#' DatabaseConnector package.
#' @param cdmDatabaseSchema Schema name where your patient-level data in OMOP CDM format resides.
#' Note that for SQL Server, this should include both the database and
#' schema name, for example 'cdm_data.dbo'.
#' @param cohortDatabaseSchema Schema name where intermediate data can be stored. You will need to have
#' write priviliges in this schema. Note that for SQL Server, this should
#' include both the database and schema name, for example 'cdm_data.dbo'.
#' @param cohortTable The name of the table that will be created in the work database schema.
#' This table will hold the exposure and outcome cohorts used in this
#' study.
#' @param oracleTempSchema Should be used in Oracle to specify a schema where the user has write
#' priviliges for storing temporary tables.
#' @param outputFolder Name of local folder to place results; make sure to use forward slashes
#' (/). Do not use a folder on a network drive since this greatly impacts
#' performance.
#' @param databaseId A short string for identifying the database (e.g.
#' 'Synpuf').
#' @param minCellCount The minimum number of subjects contributing to a count before it can be included
#' in packaged results.
#'
#' @examples
#' \dontrun{
#' connectionDetails <- createConnectionDetails(dbms = "postgresql",
#' user = "joe",
#' password = "secret",
#' server = "myserver")
#'
#' execute(connectionDetails,
#' cdmDatabaseSchema = "cdm_data",
#' cohortDatabaseSchema = "study_results",
#' cohortTable = "cohort",
#' oracleTempSchema = NULL,
#' outputFolder = "c:/temp/study_results",
#' maxCores = 4)
#' }
#'
# Generation additional table 1
#' @export
additionalResult <- function(connectionDetails = connectionDetails,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
oracleTempSchema = oracleTempSchema,
outputFolder = outputFolder,
databaseId = databaseId,
minCellCount = 1){
start <- Sys.time()
exportFolder <- file.path(outputFolder, "export")
if (!file.exists(exportFolder)) {
dir.create(exportFolder, recursive = TRUE)
}
####Cox assumption test####
popList <- list.files(file.path(outputFolder,"cmOutput"), pattern = "^StratPop_l1_s1_p1.*s1_o.*.rds")
for(i in 1:length(popList)){
if (i==1) {coxTable <- data.frame()}
popName <- popList[i]
pop <- readRDS(file.path(outputFolder,"cmOutput",popName))
exportName <- gsub("\\.rds","", gsub("StratPop_l1_s1_p1_","",popName))
if(sum(pop$outcomeCount)!=0){
try({
fit <- survival::coxph(survival::Surv(survivalTime, outcomeCount)~treatment, data = pop)
coxTest <- survival::cox.zph(fit)
coxTable1 <- as.data.frame(coxTest$table)
coxTable1$name <- exportName
coxTable <- rbind(coxTable,coxTable1)
#plotZph <- survminer::ggcoxzph(coxTest)
#if(min(coxTable1$p, na.rm = T)<0.05) ggplot2::ggsave(file.path(outputFolder,"export",paste0(exportName,"_graph.pdf" )),print(plotZph))
})
}
if (i == length(popList)) write.csv(coxTable, file.path(exportFolder,"rev_cox_assumption.csv" ))
}
####Baseline characteristics####
primaryPop <- readRDS(file.path(outputFolder, "cmOutput", "StratPop_l1_s1_p1_t874_c929_s1_o1240.rds"))
numAtRisk <- data.frame(c90=sum(primaryPop[primaryPop$survivalTime>=90,]$treatment ==0),
t90=sum(primaryPop[primaryPop$survivalTime>=90,]$treatment ==1),
c180=sum(primaryPop[primaryPop$survivalTime>=180,]$treatment ==0),
t180=sum(primaryPop[primaryPop$survivalTime>=180,]$treatment ==1),
c270=sum(primaryPop[primaryPop$survivalTime>=270,]$treatment ==0),
t270=sum(primaryPop[primaryPop$survivalTime>=270,]$treatment ==1),
c360=sum(primaryPop[primaryPop$survivalTime>=360,]$treatment ==0),
t360=sum(primaryPop[primaryPop$survivalTime>=360,]$treatment ==1))
write.csv(numAtRisk, file.path(exportFolder, "rev_number_at_risk.csv"))
popList <- list.files(file.path(outputFolder,"cmOutput"), pattern = "StratPop_l1_s1_p1_t874_c929_s1_o1240.rds|StudyPop_l1_s1_t874_c929_o1240.rds")
connectionDetails$schema <- cohortDatabaseSchema
connection <- DatabaseConnector::connect(connectionDetails)
for(i in 1:length(popList)){
if (i==1){
targetIds <- c()
comparatorIds <- c()
}
popName <- popList[i]
exportName <- gsub("\\.rds","", gsub("Pop_l1_s1_","",popName))
origTargetId <- 874
origComparatorId <- 929
outcomeId <- 1240
pop <- readRDS(file.path(outputFolder,"cmOutput", popName))
pop$cohortId <- NA
targetId <- as.numeric(sprintf("%d%04d",origTargetId,outcomeId))
comparatorId <- as.numeric(sprintf("%d%04d",origComparatorId,outcomeId))
pop$cohortId[pop$treatment==1] <- targetId
pop$cohortId[pop$treatment==0] <- comparatorId
popCohortTable <- data.frame(cohort_definition_id = pop$cohortId,
subject_id = pop$subjectId,
cohort_start_date = pop$cohortStartDate,
cohort_end_date = pop$cohortStartDate)
# Delete cohort with same cohort ID
sql <- SqlRender::loadRenderTranslateSql(sqlFilename = "DeleteCohort.sql",
packageName = "TicagrelorVsClopidogrel",
dbms = attr(connection, "dbms"),
oracleTempSchema = oracleTempSchema,
target_database_schema = cohortDatabaseSchema,
target_cohort_table = cohortTable,
target_cohort_ids = paste0(targetId, comparatorId, collapse = ","))
DatabaseConnector::executeSql(connection, sql, progressBar = FALSE, reportOverallTime = FALSE)
DatabaseConnector::insertTable(connection = connection,
tableName = cohortTable,
data = popCohortTable,
dropTableIfExists = F,
createTable = F)
targetIds <- c(targetIds, targetId)
comparatorIds <- c(comparatorIds, comparatorId)
}
DatabaseConnector::disconnect(connection)
targetName = "ticagrelor"
comparatorName = "clopidogrel"
# exportFolder <- file.path(outputFolder, "export")
# #Defining concept IDs
conditionGroupConceptIds <-
c(320128,201254,201826,432867,317309,319835,4232697,192359) #102
shorTermAcs <- c(315296, 444406, 438170, 434376, 312327) #104
drugGroupConceptIds <- c(19047423,19017067,1310149,43013024,36428260,40228152,21601784,21601823,21601665,21601744,21601461,21601855,21600095,21600713,21600744) #412
deviceConceptIds <- c(45772824) #604
#measConceptIds <- c(3038553000,3004249000,3012888000,3000963713,3004501840,3008631840,3048150842) #708
measValConceptIds <- c(3038553000,3004249000,3012888000,3000963713,3004501840,3008631840,3048150842)
for( i in 1:length(targetIds)){
targetCohortId <- targetIds[i]
comparatorCohortId <- comparatorIds[i]
targetCohortName = "ticagrelor"
comparatorCohortName= "clopidogrel"
for(endDay in c(0)){
tableSpecification <- setTableSpecification(useDemographicsGender = T,
useDemographicsAge = T,
useDemographicsAgeGroup = T,
useDemographicsRace = T,
useDemographicsEthnicity = F,
useDemographicsIndexYear = T,
useDemographicsIndexMonth = F,
useDemographicsPriorObservationTime = FALSE,
useDemographicsPostObservationTime = FALSE,
useDemographicsTimeInCohort = FALSE,
useDemographicsIndexYearMonth = F,
conceptIdsConditionOccurrenceAnyTimePrior = c(),
conceptIdsConditionOccurrenceLongTerm = conditionGroupConceptIds,
conceptIdsConditionOccurrenceMediumTerm = c(),
conceptIdsConditionOccurrenceShortTerm = shorTermAcs,
conceptIdsConditionOccurrencePrimaryInpatientAnyTimePrior = c(),
conceptIdsConditionOccurrencePrimaryInpatientLongTerm = c(),
conceptIdsConditionOccurrencePrimaryInpatientMediumTerm = c(),
conceptIdsConditionOccurrencePrimaryInpatientShortTerm = c(),
conceptIdsConditionEraAnyTimePrior = c(),
conceptIdsConditionEraLongTerm = c(),
conceptIdsConditionEraMediumTerm = c(),
conceptIdsConditionEraShortTerm = c(),
conceptIdsConditionEraOverlapping = c(),
conceptIdsConditionEraStartLongTerm = c(),
conceptIdsConditionEraStartMediumTerm = c(),
conceptIdsConditionEraStartShortTerm = c(),
conceptIdsConditionGroupEraAnyTimePrior = c(),
conceptIdsConditionGroupEraLongTerm = c(),
conceptIdsConditionGroupEraMediumTerm = c(),
conceptIdsConditionGroupEraShortTerm = shorTermAcs,
conceptIdsConditionGroupEraOverlapping = c(),
conceptIdsConditionGroupEraStartLongTerm = c(),
conceptIdsConditionGroupEraStartMediumTerm = c(),
conceptIdsConditionGroupEraStartShortTerm = c(),
conceptIdsDrugExposureAnyTimePrior = c(),
conceptIdsDrugExposureLongTerm = c(),
conceptIdsDrugExposureMediumTerm = c(),
conceptIdsDrugExposureShortTerm = c(),
conceptIdsDrugEraAnyTimePrior = c(),
conceptIdsDrugEraLongTerm = c(),
conceptIdsDrugEraMediumTerm = c(),
conceptIdsDrugEraShortTerm = c(),
conceptIdsDrugEraOverlapping = c(),
conceptIdsDrugEraStartLongTerm = c(),
conceptIdsDrugEraStartMediumTerm = c(),
conceptIdsDrugEraStartShortTerm = c(),
conceptIdsDrugGroupEraAnyTimePrior = c(),
conceptIdsDrugGroupEraLongTerm = c(),
conceptIdsDrugGroupEraMediumTerm = c(),
conceptIdsDrugGroupEraShortTerm = c(),
conceptIdsDrugGroupEraOverlapping = c(),
conceptIdsDrugGroupEraStartLongTerm = c(),
conceptIdsDrugGroupEraStartMediumTerm = c(),
conceptIdsDrugGroupEraStartShortTerm = c(),
conceptIdsProcedureOccurrenceAnyTimePrior = c(),
conceptIdsProcedureOccurrenceLongTerm = c(),
conceptIdsProcedureOccurrenceMediumTerm = c(),
conceptIdsProcedureOccurrenceShortTerm = c(),
conceptIdsDeviceExposureAnyTimePrior = c(),
conceptIdsDeviceExposureLongTerm = c(),
conceptIdsDeviceExposureMediumTerm = c(),
conceptIdsDeviceExposureShortTerm = c(),
conceptIdsMeasurementAnyTimePrior = c(),
conceptIdsMeasurementLongTerm = c(),
conceptIdsMeasurementMediumTerm = c(),
conceptIdsMeasurementShortTerm = c(),#measConceptIds,
conceptIdsMeasurementValueAnyTimePrior = c(),
conceptIdsMeasurementValueLongTerm = c(),
conceptIdsMeasurementValueMediumTerm = c(),
conceptIdsMeasurementValueShortTerm = measValConceptIds, #measConceptIds,
conceptIdsMeasurementRangeGroupAnyTimePrior = c(),
conceptIdsMeasurementRangeGroupLongTerm = c(),
conceptIdsMeasurementRangeGroupMediumTerm = c(),
conceptIdsMeasurementRangeGroupShortTerm = c(),
conceptIdsObservationAnyTimePrior = c(),
conceptIdsObservationLongTerm = c(),
conceptIdsObservationMediumTerm = c(),
conceptIdsObservationShortTerm = c(),
useCharlsonIndex = F,
useDcsi = FALSE,
useChads2 = FALSE,
useChads2Vasc = FALSE,
useHfrs = F,#T,
useDistinctConditionCountLongTerm = FALSE,
useDistinctConditionCountMediumTerm = FALSE,
useDistinctConditionCountShortTerm = FALSE,
useDistinctIngredientCountLongTerm = FALSE,
useDistinctIngredientCountMediumTerm = FALSE,
useDistinctIngredientCountShortTerm = FALSE,
useDistinctProcedureCountLongTerm = FALSE,
useDistinctProcedureCountMediumTerm = FALSE,
useDistinctProcedureCountShortTerm = FALSE,
useDistinctMeasurementCountLongTerm = FALSE,
useDistinctMeasurementCountMediumTerm = FALSE,
useDistinctMeasurementCountShortTerm = FALSE,
useDistinctObservationCountLongTerm = FALSE,
useDistinctObservationCountMediumTerm = FALSE,
useDistinctObservationCountShortTerm = FALSE,
useVisitCountLongTerm = F,
useVisitCountMediumTerm = F,
useVisitCountShortTerm = F,
useVisitConceptCountLongTerm = F,
useVisitConceptCountMediumTerm = F,
useVisitConceptCountShortTerm = F,
longTermStartDays = -365,
mediumTermStartDays = -30,
shortTermStartDays = -7,
endDays = endDay) #you can try diverse time settings
tryCatch({
comparativeCharacterization(connectionDetails = connectionDetails,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
oracleTempSchema = oracleTempSchema,
outputFolder = outputFolder,
minCellCount = minCellCount,
targetCohortId = targetCohortId,
comparatorCohortId = comparatorCohortId,#7,
outcomeCohortIds = NULL,
tableSpecification = tableSpecification,
sampleSize = NULL,
output = "one column",
percentDigits = 1,
valueDigits = 1,
stdDiffDigits = 2,
studyPopulationSetting = NULL,
fileName = file.path(exportFolder, sprintf("rev_base_char_t%s_c%s.csv",targetCohortId, comparatorCohortId)))
},
error = function(e) {
ParallelLogger::logTrace(paste0(sprintf("Generating table 1 for cohort ID %s_%s is failed. The error message:", targetCohortId, comparatorCohortId), e))},
finally = {
ParallelLogger::logTrace('Done.')})
}
}
# Add all to zip file -------------------------------------------------------------------------------
ParallelLogger::logInfo("Adding results to zip file")
zipName <- file.path(exportFolder, paste0("Results_for_revision", databaseId, ".zip"))
files <- list.files(exportFolder, pattern = "rev.*\\.csv$")
oldWd <- setwd(exportFolder)
on.exit(setwd(oldWd), add = TRUE)
DatabaseConnector::createZipFile(zipFile = zipName, files = files)
ParallelLogger::logInfo("Results are ready for sharing at:", zipName)
delta <- Sys.time() - start
ParallelLogger::logInfo(paste("Generating additional result took",
signif(delta, 3),
attr(delta, "units")))
}
#' Comparative Characterization
#'
#' @details
#' This function create the comparative table 1 for target and comparator
#'
#' @export
comparativeCharacterization <- function(connectionDetails,
cdmDatabaseSchema,
cohortDatabaseSchema = cdmDatabaseSchema,
cohortTable = "cohort",
oracleTempSchema = NULL,
outputFolder,
minCellCount = 0,
targetCohortId,
comparatorCohortId = NULL,
outcomeCohortIds = NULL,
tableSpecification = setTableSpecification(),
sampleSize = NULL,
output = "one column",
percentDigits = 1,
valueDigits = 1,
stdDiffDigits = 2,
studyPopulationSetting = NULL,
fileName = NULL){
if (!file.exists(outputFolder))
dir.create(outputFolder, recursive = TRUE)
if (!is.null(getOption("fftempdir")) && !file.exists(getOption("fftempdir"))) {
warning("fftempdir '", getOption("fftempdir"), "' not found. Attempting to create folder")
dir.create(getOption("fftempdir"), recursive = TRUE)
}
ParallelLogger::addDefaultFileLogger(file.path(outputFolder, "log.txt"))
if(is.null(outcomeCohortIds)){
targetCovData <- FeatureExtraction::getDbCovariateData(connectionDetails = connectionDetails,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
cohortId = targetCohortId,
rowIdField = "subject_id",
covariateSettings = tableSpecification$covariateSetting,
aggregated = F)
targetCovAggData <- FeatureExtraction::aggregateCovariates(targetCovData)
ParallelLogger::logInfo(sprintf("Covariates for target Id %s are extracted", targetCohortId))
if(!is.null(comparatorCohortId)){
comparatorCovData <- FeatureExtraction::getDbCovariateData(connectionDetails = connectionDetails,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
cohortId = comparatorCohortId,
rowIdField = "subject_id",
covariateSettings = tableSpecification$covariateSetting,
aggregated = F)
comparatorCovAggData <- FeatureExtraction::aggregateCovariates(comparatorCovData)
ParallelLogger::logInfo(sprintf("Covariates for comparator Id %s are extracted", comparatorCohortId))
}else {
comparatorCovData <- NULL
comparatorCovAggData <- NULL
}
table1 <- createTable1(targetCovAggData,
comparatorCovAggData,
specification = tableSpecification$tableSpec,
output = "one column",
showCounts = TRUE,
showPercent = TRUE,
percentDigits = 1,
valueDigits = 1,
stdDiffDigits = 2)
countNum <- as.numeric(gsub(",","",as.character(table1$Count)))
smallCellIndex <- which(((countNum < minCellCount) & (countNum > 0)) & (!is.na(countNum)))
if(length(smallCellIndex) > 0){
table1[smallCellIndex, 2] <- sprintf("< %d", minCellCount)
table1[smallCellIndex, 3] <- NA
}
if(!is.null(fileName)){
write.csv(table1,fileName)
ParallelLogger::logInfo(sprintf("Table 1 is saved in %s", fileName))
}
# if(!is.null(fileName)){
# write.csv(table1,fileName)
# ParallelLogger::logInfo(sprintf("Table 1 is saved in %s", fileName))
# }
}else{
stop("currently, stratification on outcome Id or incidence calculation is not supported")
}
}
# restricts to pop and saves/creates mapping
mapCovariates <- function(plpData,
population){
covariates = plpData$covariates
covariateRef = plpData$covariateRef
# restrict to population stratified by outcomes
ParallelLogger::logTrace('restricting to population according to the outcome status...')
idx <- ffbase::ffmatch(x = covariates$rowId, table = ff::as.ff(population$rowId))
idx <- ffbase::ffwhich(idx, !is.na(idx))
covariates <- covariates[idx, ]
covariateData = list(covariates = covariates,
covariateRef = covariateRef,
timeRef = plpData$timeRef,
analysisRef = plpData$analysisRef,
metaData = plpData$metaData)
class (covariateData) = "covariateData"
return(covariateData)
}
#' Set the setting for the table 1
#'
#' @details
#' This function create the setting for the table 1.
#'
#' @param useDemographicsGender = FALSE
#' @param useDemographicsAge
#' @param useDemographicsAgeGroup
#' @param useDemographicsRace
#' @param useDemographicsEthnicity
#' @param useDemographicsIndexYear
#' @param useDemographicsIndexMonth
#' @param useDemographicsPriorObservationTime
#' @param useDemographicsPostObservationTime
#' @param useDemographicsTimeInCohort
#' @param useDemographicsIndexYearMonth
#' @param conceptIdsConditionOccurrenceAnyTimePrior
#' @param conceptIdsConditionOccurrenceLongTerm
#' @param conceptIdsConditionOccurrenceMediumTerm
#' @param conceptIdsConditionOccurrenceShortTerm
#' @param conceptIdsConditionOccurrencePrimaryInpatientAnyTimePrior
#' @param conceptIdsConditionOccurrencePrimaryInpatientLongTerm
#' @param conceptIdsConditionOccurrencePrimaryInpatientMediumTerm
#' @param conceptIdsConditionOccurrencePrimaryInpatientShortTerm
#' @param conceptIdsConditionEraAnyTimePrior
#' @param conceptIdsConditionEraLongTerm
#' @param conceptIdsConditionEraMediumTerm
#' @param conceptIdsConditionEraShortTerm
#' @param conceptIdsConditionEraOverlapping
#' @param conceptIdsConditionEraStartLongTerm
#' @param conceptIdsConditionEraStartMediumTerm
#' @param conceptIdsConditionEraStartShortTerm
#' @param conceptIdsConditionGroupEraAnyTimePrior
#' @param conceptIdsConditionGroupEraLongTerm
#' @param conceptIdsConditionGroupEraMediumTerm
#' @param conceptIdsConditionGroupEraShortTerm
#' @param conceptIdsConditionGroupEraOverlapping
#' @param conceptIdsConditionGroupEraStartLongTerm
#' @param conceptIdsConditionGroupEraStartMediumTerm
#' @param conceptIdsConditionGroupEraStartShortTerm
#' @param conceptIdsDrugExposureAnyTimePrior
#' @param conceptIdsDrugExposureLongTerm
#' @param conceptIdsDrugExposureMediumTerm
#' @param conceptIdsDrugExposureShortTerm
#' @param conceptIdsDrugEraAnyTimePrior
#' @param conceptIdsDrugEraLongTerm
#' @param conceptIdsDrugEraMediumTerm
#' @param conceptIdsDrugEraShortTerm
#' @param conceptIdsDrugEraOverlapping
#' @param conceptIdsDrugEraStartLongTerm
#' @param conceptIdsDrugEraStartMediumTerm
#' @param conceptIdsDrugEraStartShortTerm
#' @param conceptIdsDrugGroupEraAnyTimePrior
#' @param conceptIdsDrugGroupEraLongTerm
#' @param conceptIdsDrugGroupEraMediumTerm
#' @param conceptIdsDrugGroupEraShortTerm
#' @param conceptIdsDrugGroupEraOverlapping
#' @param conceptIdsDrugGroupEraStartLongTerm
#' @param conceptIdsDrugGroupEraStartMediumTerm
#' @param conceptIdsDrugGroupEraStartShortTerm
#' @param conceptIdsProcedureOccurrenceAnyTimePrior
#' @param conceptIdsProcedureOccurrenceLongTerm
#' @param conceptIdsProcedureOccurrenceMediumTerm
#' @param conceptIdsProcedureOccurrenceShortTerm
#' @param conceptIdsDeviceExposureAnyTimePrior
#' @param conceptIdsDeviceExposureLongTerm
#' @param conceptIdsDeviceExposureMediumTerm
#' @param conceptIdsDeviceExposureShortTerm
#' @param conceptIdsMeasurementAnyTimePrior
#' @param conceptIdsMeasurementLongTerm
#' @param conceptIdsMeasurementMediumTerm
#' @param conceptIdsMeasurementShortTerm
#' @param conceptIdsMeasurementValueAnyTimePrior
#' @param conceptIdsMeasurementValueLongTerm
#' @param conceptIdsMeasurementValueMediumTerm
#' @param conceptIdsMeasurementValueShortTerm
#' @param conceptIdsMeasurementRangeGroupAnyTimePrior
#' @param conceptIdsMeasurementRangeGroupLongTerm
#' @param conceptIdsMeasurementRangeGroupMediumTerm
#' @param conceptIdsMeasurementRangeGroupShortTerm
#' @param conceptIdsObservationAnyTimePrior
#' @param conceptIdsObservationLongTerm
#' @param conceptIdsObservationMediumTerm
#' @param conceptIdsObservationShortTerm
#' @param useCharlsonIndex
#' @param useDcsi
#' @param useChads2
#' @param useChads2Vasc
#' @param useHfrs
#' @param useDistinctConditionCountLongTerm
#' @param useDistinctConditionCountMediumTerm
#' @param useDistinctConditionCountShortTerm
#' @param useDistinctIngredientCountLongTerm
#' @param useDistinctIngredientCountMediumTerm
#' @param useDistinctIngredientCountShortTerm
#' @param useDistinctProcedureCountLongTerm
#' @param useDistinctProcedureCountMediumTerm
#' @param useDistinctProcedureCountShortTerm
#' @param useDistinctMeasurementCountLongTerm
#' @param useDistinctMeasurementCountMediumTerm
#' @param useDistinctMeasurementCountShortTerm
#' @param useDistinctObservationCountLongTerm
#' @param useDistinctObservationCountMediumTerm
#' @param useDistinctObservationCountShortTerm
#' @param useVisitCountLongTerm
#' @param useVisitCountMediumTerm
#' @param useVisitCountShortTerm
#' @param useVisitConceptCountLongTerm
#' @param useVisitConceptCountMediumTerm
#' @param useVisitConceptCountShortTerm
#' @param longTermStartDays
#' @param mediumTermStartDays
#' @param shortTermStartDays
#' @param endDays
#'
#' @return
#' An object of type \code{tableSpecification}, to be used in other functions.
#'
#' @export
setTableSpecification <- function(useDemographicsGender = FALSE,
useDemographicsAge = FALSE,
useDemographicsAgeGroup = FALSE,
useDemographicsRace = FALSE,
useDemographicsEthnicity = FALSE,
useDemographicsIndexYear = FALSE,
useDemographicsIndexMonth = FALSE,
useDemographicsPriorObservationTime = FALSE,
useDemographicsPostObservationTime = FALSE,
useDemographicsTimeInCohort = FALSE,
useDemographicsIndexYearMonth = FALSE,
conceptIdsConditionOccurrenceAnyTimePrior = c(),
conceptIdsConditionOccurrenceLongTerm = c(),
conceptIdsConditionOccurrenceMediumTerm = c(),
conceptIdsConditionOccurrenceShortTerm = c(),
conceptIdsConditionOccurrencePrimaryInpatientAnyTimePrior = c(),
conceptIdsConditionOccurrencePrimaryInpatientLongTerm = c(),
conceptIdsConditionOccurrencePrimaryInpatientMediumTerm = c(),
conceptIdsConditionOccurrencePrimaryInpatientShortTerm = c(),
conceptIdsConditionEraAnyTimePrior = c(),
conceptIdsConditionEraLongTerm = c(),
conceptIdsConditionEraMediumTerm = c(),
conceptIdsConditionEraShortTerm = c(),
conceptIdsConditionEraOverlapping = c(),
conceptIdsConditionEraStartLongTerm = c(),
conceptIdsConditionEraStartMediumTerm = c(),
conceptIdsConditionEraStartShortTerm = c(),
conceptIdsConditionGroupEraAnyTimePrior = c(),
conceptIdsConditionGroupEraLongTerm = c(),
conceptIdsConditionGroupEraMediumTerm = c(),
conceptIdsConditionGroupEraShortTerm = c(),
conceptIdsConditionGroupEraOverlapping = c(),
conceptIdsConditionGroupEraStartLongTerm = c(),
conceptIdsConditionGroupEraStartMediumTerm = c(),
conceptIdsConditionGroupEraStartShortTerm = c(),
conceptIdsDrugExposureAnyTimePrior = c(),
conceptIdsDrugExposureLongTerm = c(),
conceptIdsDrugExposureMediumTerm = c(),
conceptIdsDrugExposureShortTerm = c(),
conceptIdsDrugEraAnyTimePrior = c(),
conceptIdsDrugEraLongTerm = c(),
conceptIdsDrugEraMediumTerm = c(),
conceptIdsDrugEraShortTerm = c(),
conceptIdsDrugEraOverlapping = c(),
conceptIdsDrugEraStartLongTerm = c(),
conceptIdsDrugEraStartMediumTerm = c(),
conceptIdsDrugEraStartShortTerm = c(),
conceptIdsDrugGroupEraAnyTimePrior = c(),
conceptIdsDrugGroupEraLongTerm = c(),
conceptIdsDrugGroupEraMediumTerm = c(),
conceptIdsDrugGroupEraShortTerm = c(),
conceptIdsDrugGroupEraOverlapping = c(),
conceptIdsDrugGroupEraStartLongTerm = c(),
conceptIdsDrugGroupEraStartMediumTerm = c(),
conceptIdsDrugGroupEraStartShortTerm = c(),
conceptIdsProcedureOccurrenceAnyTimePrior = c(),
conceptIdsProcedureOccurrenceLongTerm = c(),
conceptIdsProcedureOccurrenceMediumTerm = c(),
conceptIdsProcedureOccurrenceShortTerm = c(),
conceptIdsDeviceExposureAnyTimePrior = c(),
conceptIdsDeviceExposureLongTerm = c(),
conceptIdsDeviceExposureMediumTerm = c(),
conceptIdsDeviceExposureShortTerm = c(),
conceptIdsMeasurementAnyTimePrior = c(),
conceptIdsMeasurementLongTerm = c(),
conceptIdsMeasurementMediumTerm = c(),
conceptIdsMeasurementShortTerm = c(),
conceptIdsMeasurementValueAnyTimePrior = c(),
conceptIdsMeasurementValueLongTerm = c(),
conceptIdsMeasurementValueMediumTerm = c(),
conceptIdsMeasurementValueShortTerm = c(),
conceptIdsMeasurementRangeGroupAnyTimePrior = c(),
conceptIdsMeasurementRangeGroupLongTerm = c(),
conceptIdsMeasurementRangeGroupMediumTerm = c(),
conceptIdsMeasurementRangeGroupShortTerm = c(),
conceptIdsObservationAnyTimePrior = c(),
conceptIdsObservationLongTerm = c(),
conceptIdsObservationMediumTerm = c(),
conceptIdsObservationShortTerm = c(),
useCharlsonIndex = FALSE,
useDcsi = FALSE,
useChads2 = FALSE,
useChads2Vasc = FALSE,
useHfrs = FALSE,
useDistinctConditionCountLongTerm = FALSE,
useDistinctConditionCountMediumTerm = FALSE,
useDistinctConditionCountShortTerm = FALSE,
useDistinctIngredientCountLongTerm = FALSE,
useDistinctIngredientCountMediumTerm = FALSE,
useDistinctIngredientCountShortTerm = FALSE,
useDistinctProcedureCountLongTerm = FALSE,
useDistinctProcedureCountMediumTerm = FALSE,
useDistinctProcedureCountShortTerm = FALSE,
useDistinctMeasurementCountLongTerm = FALSE,
useDistinctMeasurementCountMediumTerm = FALSE,
useDistinctMeasurementCountShortTerm = FALSE,
useDistinctObservationCountLongTerm = FALSE,
useDistinctObservationCountMediumTerm = FALSE,
useDistinctObservationCountShortTerm = FALSE,
useVisitCountLongTerm = FALSE,
useVisitCountMediumTerm = FALSE,
useVisitCountShortTerm = FALSE,
useVisitConceptCountLongTerm = FALSE,
useVisitConceptCountMediumTerm = FALSE,
useVisitConceptCountShortTerm = FALSE,
longTermStartDays = -365,
mediumTermStartDays = -180,
shortTermStartDays = -30,
endDays = 0){
covariateSetting <- FeatureExtraction::createCovariateSettings(useDemographicsGender = useDemographicsGender,
useDemographicsAge = useDemographicsAge,
useDemographicsAgeGroup = useDemographicsAgeGroup,
useDemographicsRace = useDemographicsRace,
useDemographicsEthnicity = useDemographicsEthnicity,
useDemographicsIndexYear = useDemographicsIndexYear,
useDemographicsIndexMonth = useDemographicsIndexMonth,
useDemographicsPriorObservationTime = useDemographicsPriorObservationTime,
useDemographicsPostObservationTime = useDemographicsPostObservationTime,
useDemographicsTimeInCohort = useDemographicsTimeInCohort,
useDemographicsIndexYearMonth = useDemographicsIndexYearMonth,
useConditionOccurrenceAnyTimePrior = as.logical(length(conceptIdsConditionOccurrenceAnyTimePrior)),
useConditionOccurrenceLongTerm = as.logical(length(conceptIdsConditionOccurrenceLongTerm)),
useConditionOccurrenceMediumTerm = as.logical(length(conceptIdsConditionOccurrenceMediumTerm)),
useConditionOccurrenceShortTerm = as.logical(length(conceptIdsConditionOccurrenceShortTerm)),
useConditionOccurrencePrimaryInpatientAnyTimePrior = as.logical(length(conceptIdsConditionOccurrencePrimaryInpatientAnyTimePrior)),
useConditionOccurrencePrimaryInpatientLongTerm = as.logical(length(conceptIdsConditionOccurrencePrimaryInpatientLongTerm)),
useConditionOccurrencePrimaryInpatientMediumTerm = as.logical(length(conceptIdsConditionOccurrencePrimaryInpatientMediumTerm)),
useConditionOccurrencePrimaryInpatientShortTerm = as.logical(length(conceptIdsConditionOccurrencePrimaryInpatientShortTerm)),
useConditionEraAnyTimePrior = as.logical(length(conceptIdsConditionEraAnyTimePrior)),
useConditionEraLongTerm = as.logical(length(conceptIdsConditionEraLongTerm)),
useConditionEraMediumTerm = as.logical(length(conceptIdsConditionEraMediumTerm)),
useConditionEraShortTerm = as.logical(length(conceptIdsConditionEraShortTerm)),
useConditionEraOverlapping = as.logical(length(conceptIdsConditionEraOverlapping)),
useConditionEraStartLongTerm = as.logical(length(conceptIdsConditionEraStartLongTerm)),
useConditionEraStartMediumTerm = as.logical(length(conceptIdsConditionEraStartMediumTerm)),
useConditionEraStartShortTerm = as.logical(length(conceptIdsConditionEraStartShortTerm)),
useConditionGroupEraAnyTimePrior = as.logical(length(conceptIdsConditionGroupEraAnyTimePrior)),
useConditionGroupEraLongTerm = as.logical(length(conceptIdsConditionGroupEraLongTerm)),
useConditionGroupEraMediumTerm = as.logical(length(conceptIdsConditionGroupEraMediumTerm)),
useConditionGroupEraShortTerm = as.logical(length(conceptIdsConditionGroupEraShortTerm)),
useConditionGroupEraOverlapping = as.logical(length(conceptIdsConditionGroupEraOverlapping)),
useConditionGroupEraStartLongTerm = as.logical(length(conceptIdsConditionGroupEraStartLongTerm)),
useConditionGroupEraStartMediumTerm = as.logical(length(conceptIdsConditionGroupEraStartMediumTerm)),
useConditionGroupEraStartShortTerm = as.logical(length(conceptIdsConditionGroupEraStartShortTerm)),
useDrugExposureAnyTimePrior = as.logical(length(conceptIdsDrugExposureAnyTimePrior)),
useDrugExposureLongTerm = as.logical(length(conceptIdsDrugExposureLongTerm)),
useDrugExposureMediumTerm = as.logical(length(conceptIdsDrugExposureMediumTerm)),
useDrugExposureShortTerm = as.logical(length(conceptIdsDrugExposureShortTerm)),
useDrugEraAnyTimePrior = as.logical(length(conceptIdsDrugEraAnyTimePrior)),
useDrugEraLongTerm = as.logical(length(conceptIdsDrugEraLongTerm)),
useDrugEraMediumTerm = as.logical(length(conceptIdsDrugEraMediumTerm)),
useDrugEraShortTerm = as.logical(length(conceptIdsDrugEraShortTerm)),
useDrugEraOverlapping = as.logical(length(conceptIdsDrugEraOverlapping)),
useDrugEraStartLongTerm = as.logical(length(conceptIdsDrugEraStartLongTerm)),
useDrugEraStartMediumTerm = as.logical(length(conceptIdsDrugEraStartMediumTerm)),
useDrugEraStartShortTerm = as.logical(length(conceptIdsDrugEraStartShortTerm)),
useDrugGroupEraAnyTimePrior = as.logical(length(conceptIdsDrugGroupEraAnyTimePrior)),
useDrugGroupEraLongTerm = as.logical(length(conceptIdsDrugGroupEraLongTerm)),
useDrugGroupEraMediumTerm = as.logical(length(conceptIdsDrugGroupEraMediumTerm)),
useDrugGroupEraShortTerm = as.logical(length(conceptIdsDrugGroupEraShortTerm)),
useDrugGroupEraOverlapping = as.logical(length(conceptIdsDrugGroupEraOverlapping)),
useDrugGroupEraStartLongTerm = as.logical(length(conceptIdsDrugGroupEraStartLongTerm)),
useDrugGroupEraStartMediumTerm = as.logical(length(conceptIdsDrugGroupEraStartMediumTerm)),
useDrugGroupEraStartShortTerm = as.logical(length(conceptIdsDrugGroupEraStartShortTerm)),
useProcedureOccurrenceAnyTimePrior = as.logical(length(conceptIdsProcedureOccurrenceAnyTimePrior)),
useProcedureOccurrenceLongTerm = as.logical(length(conceptIdsProcedureOccurrenceLongTerm)),
useProcedureOccurrenceMediumTerm = as.logical(length(conceptIdsProcedureOccurrenceMediumTerm)),
useProcedureOccurrenceShortTerm = as.logical(length(conceptIdsProcedureOccurrenceShortTerm)),
useDeviceExposureAnyTimePrior = as.logical(length(conceptIdsDeviceExposureAnyTimePrior)),
useDeviceExposureLongTerm = as.logical(length(conceptIdsDeviceExposureLongTerm)),
useDeviceExposureMediumTerm = as.logical(length(conceptIdsDeviceExposureMediumTerm)),
useDeviceExposureShortTerm = as.logical(length(conceptIdsDeviceExposureShortTerm)),
useMeasurementAnyTimePrior = as.logical(length(conceptIdsMeasurementAnyTimePrior)),
useMeasurementLongTerm = as.logical(length(conceptIdsMeasurementLongTerm)),
useMeasurementMediumTerm = as.logical(length(conceptIdsMeasurementMediumTerm)),
useMeasurementShortTerm = as.logical(length(conceptIdsMeasurementShortTerm)),
useMeasurementValueAnyTimePrior = as.logical(length(conceptIdsMeasurementValueAnyTimePrior)),
useMeasurementValueLongTerm = as.logical(length(conceptIdsMeasurementValueLongTerm)),
useMeasurementValueMediumTerm = as.logical(length(conceptIdsMeasurementValueMediumTerm)),
useMeasurementValueShortTerm = as.logical(length(conceptIdsMeasurementValueShortTerm)),
useMeasurementRangeGroupAnyTimePrior = as.logical(length(conceptIdsMeasurementRangeGroupAnyTimePrior)),
useMeasurementRangeGroupLongTerm = as.logical(length(conceptIdsMeasurementRangeGroupLongTerm)),
useMeasurementRangeGroupMediumTerm = as.logical(length(conceptIdsMeasurementRangeGroupMediumTerm)),
useMeasurementRangeGroupShortTerm = as.logical(length(conceptIdsMeasurementRangeGroupShortTerm)),
useObservationAnyTimePrior = as.logical(length(conceptIdsObservationAnyTimePrior)),
useObservationLongTerm = as.logical(length(conceptIdsObservationLongTerm)),
useObservationMediumTerm = as.logical(length(conceptIdsObservationMediumTerm)),
useObservationShortTerm = as.logical(length(conceptIdsObservationShortTerm)),
useCharlsonIndex = useCharlsonIndex,
useDcsi = useDcsi,
useChads2 = useChads2,
useChads2Vasc = useChads2Vasc,
useHfrs = useHfrs,
useDistinctConditionCountLongTerm = useDistinctConditionCountLongTerm,
useDistinctConditionCountMediumTerm = useDistinctConditionCountMediumTerm,
useDistinctConditionCountShortTerm = useDistinctConditionCountShortTerm,
useDistinctIngredientCountLongTerm = useDistinctIngredientCountLongTerm,
useDistinctIngredientCountMediumTerm = useDistinctIngredientCountMediumTerm,
useDistinctIngredientCountShortTerm = useDistinctIngredientCountShortTerm,
useDistinctProcedureCountLongTerm = useDistinctProcedureCountLongTerm,
useDistinctProcedureCountMediumTerm = useDistinctProcedureCountMediumTerm,
useDistinctProcedureCountShortTerm = useDistinctProcedureCountShortTerm,
useDistinctMeasurementCountLongTerm = useDistinctMeasurementCountLongTerm,
useDistinctMeasurementCountMediumTerm = useDistinctMeasurementCountMediumTerm,
useDistinctMeasurementCountShortTerm = useDistinctMeasurementCountShortTerm,
useDistinctObservationCountLongTerm = useDistinctObservationCountLongTerm,
useDistinctObservationCountMediumTerm = useDistinctObservationCountMediumTerm,
useDistinctObservationCountShortTerm = useDistinctObservationCountShortTerm,
useVisitCountLongTerm = useVisitCountLongTerm,
useVisitCountMediumTerm = useVisitCountMediumTerm,
useVisitCountShortTerm = useVisitCountShortTerm,
useVisitConceptCountLongTerm = useVisitConceptCountLongTerm,
useVisitConceptCountMediumTerm = useVisitConceptCountMediumTerm,
useVisitConceptCountShortTerm = useVisitConceptCountShortTerm,
longTermStartDays = longTermStartDays,
mediumTermStartDays = mediumTermStartDays,
shortTermStartDays = shortTermStartDays,
endDays = endDays)
label <- c()
analysisId <- c()
covariateIds <- c()
if(useDemographicsGender){
label <- c(label, "Gender")
analysisId <- c(analysisId, 1)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",8532,1),collapse=","))
}
if(useDemographicsAge){
label <- c(label, "Age")
analysisId <- c(analysisId, 2)
covariateIds <- c(covariateIds, "")
}
if(useDemographicsAgeGroup){
label <- c(label, "Age Group")
analysisId <- c(analysisId, 3)
covariateIds <- c(covariateIds, "")
}
if(useDemographicsRace){
label <- c(label, "Race")
analysisId <- c(analysisId, 4)
covariateIds <- c(covariateIds, "")
}
if(useDemographicsEthnicity){
label <- c(label, "Ethnicity")
analysisId <- c(analysisId, 5)
covariateIds <- c(covariateIds, "")
}
if(useDemographicsIndexYear){
label <- c(label, "Index year")
analysisId <- c(analysisId, 6)
covariateIds <- c(covariateIds, "")
}
if(useDemographicsIndexMonth){
label <- c(label, "Index month")
analysisId <- c(analysisId, 7)
covariateIds <- c(covariateIds, "")
}
if(useDemographicsPriorObservationTime){
label <- c(label, "Prior obesrvation time")
analysisId <- c(analysisId, 8)
covariateIds <- c(covariateIds, "")
}
if(useDemographicsPostObservationTime){
label <- c(label, "Post observation time")
analysisId <- c(analysisId, 9)
covariateIds <- c(covariateIds, "")
}
if(useDemographicsTimeInCohort){
label <- c(label, "Time in cohort")
analysisId <- c(analysisId, 10)
covariateIds <- c(covariateIds, "")
}
if(useDemographicsIndexYearMonth){
label <- c(label, "Index year month")
analysisId <- c(analysisId, 11)
covariateIds <- c(covariateIds, "")
}
if(length(conceptIdsConditionOccurrenceAnyTimePrior)){
label <- c(label, "ConditionOccurrenceAnyTimePrior")
analysisId <- c(analysisId, 101)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionOccurrenceAnyTimePrior,101),collapse=","))
}
if(length(conceptIdsConditionOccurrenceLongTerm)){
label <- c(label, "ConditionOccurrenceLongTerm")
analysisId <- c(analysisId, 102)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionOccurrenceLongTerm,102),collapse=","))
}
if(length(conceptIdsConditionOccurrenceMediumTerm)){
label <- c(label, "ConditionOccurrenceMediumTerm")
analysisId <- c(analysisId, 103)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionOccurrenceMediumTerm,103),collapse=","))
}
if(length(conceptIdsConditionOccurrenceShortTerm)){
label <- c(label, "ConditionOccurrenceShortTerm")
analysisId <- c(analysisId, 104)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionOccurrenceShortTerm,104),collapse=","))
}
if(length(conceptIdsConditionOccurrencePrimaryInpatientAnyTimePrior)){
label <- c(label, "ConditionOccurrencePrimaryInpatientAnyTimePrior")
analysisId <- c(analysisId, 105)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionOccurrencePrimaryInpatientAnyTimePrior,105),collapse=","))
}
if(length(conceptIdsConditionOccurrencePrimaryInpatientLongTerm)){
label <- c(label, "ConditionOccurrencePrimaryInpatientLongTerm")
analysisId <- c(analysisId, 106)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionOccurrencePrimaryInpatientLongTerm,106),collapse=","))
}
if(length(conceptIdsConditionOccurrencePrimaryInpatientMediumTerm)){
label <- c(label, "ConditionOccurrencePrimaryInpatientMediumTerm")
analysisId <- c(analysisId, 107)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionOccurrencePrimaryInpatientMediumTerm,107),collapse=","))
}
if(length(conceptIdsConditionOccurrencePrimaryInpatientShortTerm)){
label <- c(label, "ConditionOccurrencePrimaryInpatientShortTerm")
analysisId <- c(analysisId, 108)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionOccurrencePrimaryInpatientShortTerm,108),collapse=","))
}
if(length(conceptIdsConditionEraAnyTimePrior)){
label <- c(label, "ConditionEraAnyTimePrior")
analysisId <- c(analysisId, 201)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionEraAnyTimePrior,201),collapse=","))
}
if(length(conceptIdsConditionEraLongTerm)){
label <- c(label, "ConditionEraLongTerm")
analysisId <- c(analysisId, 202)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionEraLongTerm,202),collapse=","))
}
if(length(conceptIdsConditionEraMediumTerm)){
label <- c(label, "ConditionEraMediumTerm")
analysisId <- c(analysisId, 203)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionEraMediumTerm,203),collapse=","))
}
if(length(conceptIdsConditionEraShortTerm)){
label <- c(label, "ConditionEraShortTerm")
analysisId <- c(analysisId, 204)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionEraShortTerm,204),collapse=","))
}
if(length(conceptIdsConditionEraOverlapping)){
label <- c(label, "ConditionEraOverlapping")
analysisId <- c(analysisId, 205)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionEraOverlapping,205),collapse=","))
}
if(length(conceptIdsConditionEraStartLongTerm)){
label <- c(label, "ConditionEraStartLongTerm")
analysisId <- c(analysisId, 206)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionEraStartLongTerm,206),collapse=","))
}
if(length(conceptIdsConditionEraStartMediumTerm)){
label <- c(label, "ConditionEraStartMediumTerm")
analysisId <- c(analysisId, 207)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionEraStartMediumTerm,207),collapse=","))
}
if(length(conceptIdsConditionEraStartShortTerm)){
label <- c(label, "ConditionEraStartShortTerm")
analysisId <- c(analysisId, 208)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionEraStartShortTerm,208),collapse=","))
}
if(length(conceptIdsConditionGroupEraAnyTimePrior)){
label <- c(label, "ConditionGroupEraAnyTimePrior")
analysisId <- c(analysisId, 209)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionGroupEraAnyTimePrior,209),collapse=","))
}
if(length(conceptIdsConditionGroupEraLongTerm)){
label <- c(label, "ConditionGroupEraLongTerm")
analysisId <- c(analysisId, 210)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionGroupEraLongTerm,210),collapse=","))
}
if(length(conceptIdsConditionGroupEraMediumTerm)){
label <- c(label, "ConditionGroupEraMediumTerm")
analysisId <- c(analysisId, 211)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionGroupEraMediumTerm,211),collapse=","))
}
if(length(conceptIdsConditionGroupEraShortTerm)){
label <- c(label, "ConditionGroupEraShortTerm")
analysisId <- c(analysisId, 212)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionGroupEraShortTerm,212),collapse=","))
}
if(length(conceptIdsConditionGroupEraOverlapping)){
label <- c(label, "ConditionGroupEraOverlapping")
analysisId <- c(analysisId, 213)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionGroupEraOverlapping,213),collapse=","))
}
if(length(conceptIdsConditionGroupEraStartLongTerm)){
label <- c(label, "ConditionGroupEraStartLongTerm")
analysisId <- c(analysisId, 214)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionGroupEraStartLongTerm,214),collapse=","))
}
if(length(conceptIdsConditionGroupEraStartMediumTerm)){
label <- c(label, "ConditionGroupEraStartMediumTerm")
analysisId <- c(analysisId, 215)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionGroupEraStartMediumTerm,215),collapse=","))
}
if(length(conceptIdsConditionGroupEraStartShortTerm)){
label <- c(label, "ConditionGroupEraStartShortTerm")
analysisId <- c(analysisId, 216)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionGroupEraStartShortTerm,216),collapse=","))
}
if(length(conceptIdsDrugExposureAnyTimePrior)){
label <- c(label, "DrugExposureAnyTimePrior")
analysisId <- c(analysisId, 301)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugExposureAnyTimePrior,301),collapse=","))
}
if(length(conceptIdsDrugExposureLongTerm)){
label <- c(label, "DrugExposureLongTerm")
analysisId <- c(analysisId, 302)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugExposureLongTerm,302),collapse=","))
}
if(length(conceptIdsDrugExposureMediumTerm)){
label <- c(label, "DrugExposureMediumTerm")
analysisId <- c(analysisId, 303)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugExposureMediumTerm,303),collapse=","))
}
if(length(conceptIdsDrugExposureShortTerm)){
label <- c(label, "DrugExposureShortTerm")
analysisId <- c(analysisId, 304)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugExposureShortTerm,304),collapse=","))
}
if(length(conceptIdsDrugEraAnyTimePrior)){
label <- c(label, "DrugEraAnyTimePrior")
analysisId <- c(analysisId, 401)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugEraAnyTimePrior,401),collapse=","))
}
if(length(conceptIdsDrugEraLongTerm)){
label <- c(label, "DrugEraLongTerm")
analysisId <- c(analysisId, 402)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugEraLongTerm,402),collapse=","))
}
if(length(conceptIdsDrugEraMediumTerm)){
label <- c(label, "DrugEraMediumTerm")
analysisId <- c(analysisId, 403)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugEraMediumTerm,403),collapse=","))
}
if(length(conceptIdsDrugEraShortTerm)){
label <- c(label, "DrugEraShortTerm")
analysisId <- c(analysisId, 404)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugEraShortTerm,404),collapse=","))
}
if(length(conceptIdsDrugEraOverlapping)){
label <- c(label, "DrugEraOverlapping")
analysisId <- c(analysisId, 405)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugEraOverlapping,405),collapse=","))
}
if(length(conceptIdsDrugEraStartLongTerm)){
label <- c(label, "DrugEraStartLongTerm")
analysisId <- c(analysisId, 406)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugEraStartLongTerm,406),collapse=","))
}
if(length(conceptIdsDrugEraStartMediumTerm)){
label <- c(label, "DrugEraStartMediumTerm")
analysisId <- c(analysisId, 407)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugEraStartMediumTerm,407),collapse=","))
}
if(length(conceptIdsDrugEraStartShortTerm)){
label <- c(label, "DrugEraStartShortTerm")
analysisId <- c(analysisId, 408)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugEraStartShortTerm,408),collapse=","))
}
if(length(conceptIdsDrugGroupEraAnyTimePrior)){
label <- c(label, "DrugGroupEraAnyTimePrior")
analysisId <- c(analysisId, 409)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugGroupEraAnyTimePrior,409),collapse=","))
}
if(length(conceptIdsDrugGroupEraLongTerm)){
label <- c(label, "DrugGroupEraLongTerm")
analysisId <- c(analysisId, 410)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugGroupEraLongTerm,410),collapse=","))
}
if(length(conceptIdsDrugGroupEraMediumTerm)){
label <- c(label, "DrugGroupEraMediumTerm")
analysisId <- c(analysisId, 411)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugGroupEraMediumTerm,411),collapse=","))
}
if(length(conceptIdsDrugGroupEraShortTerm)){
label <- c(label, "DrugGroupEraShortTerm")
analysisId <- c(analysisId, 412)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugGroupEraShortTerm,412),collapse=","))
}
if(length(conceptIdsDrugGroupEraOverlapping)){
label <- c(label, "DrugGroupEraOverlapping")
analysisId <- c(analysisId, 413)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugGroupEraOverlapping,413),collapse=","))
}
if(length(conceptIdsDrugGroupEraStartLongTerm)){
label <- c(label, "DrugGroupEraStartLongTerm")
analysisId <- c(analysisId, 414)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugGroupEraStartLongTerm,414),collapse=","))
}
if(length(conceptIdsDrugGroupEraStartMediumTerm)){
label <- c(label, "DrugGroupEraStartMediumTerm")
analysisId <- c(analysisId, 415)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugGroupEraStartMediumTerm,415),collapse=","))
}
if(length(conceptIdsDrugGroupEraStartShortTerm)){
label <- c(label, "DrugGroupEraStartShortTerm")
analysisId <- c(analysisId, 416)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugGroupEraStartShortTerm,416),collapse=","))
}
if(length(conceptIdsProcedureOccurrenceAnyTimePrior)){
label <- c(label, "ProcedureOccurrenceAnyTimePrior")
analysisId <- c(analysisId, 501)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsProcedureOccurrenceAnyTimePrior,501),collapse=","))
}
if(length(conceptIdsProcedureOccurrenceLongTerm)){
label <- c(label, "ProcedureOccurrenceLongTerm")
analysisId <- c(analysisId, 502)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsProcedureOccurrenceLongTerm,502),collapse=","))
}
if(length(conceptIdsProcedureOccurrenceMediumTerm)){
label <- c(label, "ProcedureOccurrenceMediumTerm")
analysisId <- c(analysisId, 503)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsProcedureOccurrenceMediumTerm,503),collapse=","))
}
if(length(conceptIdsProcedureOccurrenceShortTerm)){
label <- c(label, "ProcedureOccurrenceShortTerm")
analysisId <- c(analysisId, 504)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsProcedureOccurrenceShortTerm,504),collapse=","))
}
if(length(conceptIdsDeviceExposureAnyTimePrior)){
label <- c(label, "DeviceExposureAnyTimePrior")
analysisId <- c(analysisId, 601)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDeviceExposureAnyTimePrior,601),collapse=","))
}
if(length(conceptIdsDeviceExposureLongTerm)){
label <- c(label, "DeviceExposureLongTerm")
analysisId <- c(analysisId, 602)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDeviceExposureLongTerm,602),collapse=","))
}
if(length(conceptIdsDeviceExposureMediumTerm)){
label <- c(label, "DeviceExposureMediumTerm")
analysisId <- c(analysisId, 603)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDeviceExposureMediumTerm,603),collapse=","))
}
if(length(conceptIdsDeviceExposureShortTerm)){
label <- c(label, "DeviceExposureShortTerm")
analysisId <- c(analysisId, 604)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDeviceExposureShortTerm,604),collapse=","))
}
if(length(conceptIdsMeasurementAnyTimePrior)){
label <- c(label, "MeasurementAnyTimePrior")
analysisId <- c(analysisId, 701)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsMeasurementAnyTimePrior,701),collapse=","))
}
if(length(conceptIdsMeasurementLongTerm)){
label <- c(label, "MeasurementLongTerm")
analysisId <- c(analysisId, 702)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsMeasurementLongTerm,702),collapse=","))
}
if(length(conceptIdsMeasurementMediumTerm)){
label <- c(label, "MeasurementMediumTerm")
analysisId <- c(analysisId, 703)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsMeasurementMediumTerm,703),collapse=","))
}
if(length(conceptIdsMeasurementShortTerm)){
label <- c(label, "MeasurementShortTerm")
analysisId <- c(analysisId, 704)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsMeasurementShortTerm,704),collapse=","))
}
if(length(conceptIdsMeasurementValueAnyTimePrior)){
label <- c(label, "MeasurementValueAnyTimePrior")
analysisId <- c(analysisId, 705)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsMeasurementValueAnyTimePrior,705),collapse=","))
}
if(length(conceptIdsMeasurementValueLongTerm)){
label <- c(label, "MeasurementValueLongTerm")
analysisId <- c(analysisId, 706)
covariateIds <- c(covariateIds, paste0(sprintf("%s%03d",conceptIdsMeasurementValueLongTerm,706),collapse=","))
}
if(length(conceptIdsMeasurementValueMediumTerm)){
label <- c(label, "MeasurementValueMediumTerm")
analysisId <- c(analysisId, 707)
covariateIds <- c(covariateIds, paste0(sprintf("%s%03d",conceptIdsMeasurementValueMediumTerm,707),collapse=","))
}
if(length(conceptIdsMeasurementValueShortTerm)){
label <- c(label, "MeasurementValueShortTerm")
analysisId <- c(analysisId, 708)
covariateIds <- c(covariateIds, paste0(sprintf("%s%03d",conceptIdsMeasurementValueShortTerm,708),collapse=","))
}
if(length(conceptIdsMeasurementRangeGroupAnyTimePrior)){
label <- c(label, "MeasurementRangeGroupAnyTimePrior")
analysisId <- c(analysisId, 709)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsMeasurementRangeGroupAnyTimePrior,709),collapse=","))
}
if(length(conceptIdsMeasurementRangeGroupLongTerm)){
label <- c(label, "MeasurementRangeGroupLongTerm")
analysisId <- c(analysisId, 710)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsMeasurementRangeGroupLongTerm,710),collapse=","))
}
if(length(conceptIdsMeasurementRangeGroupMediumTerm)){
label <- c(label, "MeasurementRangeGroupMediumTerm")
analysisId <- c(analysisId, 711)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsMeasurementRangeGroupMediumTerm,711),collapse=","))
}
if(length(conceptIdsMeasurementRangeGroupShortTerm)){
label <- c(label, "MeasurementRangeGroupShortTerm")
analysisId <- c(analysisId, 712)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsMeasurementRangeGroupShortTerm,712),collapse=","))
}
if(length(conceptIdsObservationAnyTimePrior)){
label <- c(label, "ObservationAnyTimePrior")
analysisId <- c(analysisId, 801)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsObservationAnyTimePrior,801),collapse=","))
}
if(length(conceptIdsObservationLongTerm)){
label <- c(label, "ObservationLongTerm")
analysisId <- c(analysisId, 802)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsObservationLongTerm,802),collapse=","))
}
if(length(conceptIdsObservationMediumTerm)){
label <- c(label, "ObservationMediumTerm")
analysisId <- c(analysisId, 803)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsObservationMediumTerm,803),collapse=","))
}
if(length(conceptIdsObservationShortTerm)){
label <- c(label, "ObservationShortTerm")
analysisId <- c(analysisId, 804)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsObservationShortTerm,804),collapse=","))
}
if(useCharlsonIndex){
label <- c(label, "CharlsonIndex")
analysisId <- c(analysisId, 901)
covariateIds <- c(covariateIds, "")
}
if(useDcsi){
label <- c(label, "Dcsi")
analysisId <- c(analysisId, 902)
covariateIds <- c(covariateIds, "")
}
if(useChads2){
label <- c(label, "Chads2")
analysisId <- c(analysisId, 903)
covariateIds <- c(covariateIds, "")
}
if(useChads2Vasc){
label <- c(label, "Chads2Vasc")
analysisId <- c(analysisId, 904)
covariateIds <- c(covariateIds, "")
}
if(useHfrs){
label <- c(label, "Hfrs")
analysisId <- c(analysisId, 926)
covariateIds <- c(covariateIds, "")
}
if(useDistinctConditionCountLongTerm){
label <- c(label, "DistinctConditionCountLongTerm")
analysisId <- c(analysisId, 905)
covariateIds <- c(covariateIds, "")
}
if(useDistinctConditionCountMediumTerm){
label <- c(label, "DistinctConditionCountMediumTerm")
analysisId <- c(analysisId, 906)
covariateIds <- c(covariateIds, "")
}
if(useDistinctConditionCountShortTerm){
label <- c(label, "DistinctConditionCountShortTerm")
analysisId <- c(analysisId, 907)
covariateIds <- c(covariateIds, "")
}
if(useDistinctIngredientCountLongTerm){
label <- c(label, "DistinctIngredientCountLongTerm")
analysisId <- c(analysisId, 908)
covariateIds <- c(covariateIds, "")
}
if(useDistinctIngredientCountMediumTerm){
label <- c(label, "DistinctIngredientCountMediumTerm")
analysisId <- c(analysisId, 909)
covariateIds <- c(covariateIds, "")
}
if(useDistinctIngredientCountShortTerm){
label <- c(label, "DistinctIngredientCountShortTerm")
analysisId <- c(analysisId, 910)
covariateIds <- c(covariateIds, "")
}
if(useDistinctProcedureCountLongTerm){
label <- c(label, "DistinctProcedureCountLongTerm")
analysisId <- c(analysisId, 911)
covariateIds <- c(covariateIds, "")
}
if(useDistinctProcedureCountMediumTerm){
label <- c(label, "DistinctProcedureCountMediumTerm")
analysisId <- c(analysisId, 912)
covariateIds <- c(covariateIds, "")
}
if(useDistinctProcedureCountShortTerm){
label <- c(label, "DistinctProcedureCountShortTerm")
analysisId <- c(analysisId, 913)
covariateIds <- c(covariateIds, "")
}
if(useDistinctMeasurementCountLongTerm){
label <- c(label, "DistinctMeasurementCountLongTerm")
analysisId <- c(analysisId, 914)
covariateIds <- c(covariateIds, "")
}
if(useDistinctMeasurementCountMediumTerm){
label <- c(label, "DistinctMeasurementCountMediumTerm")
analysisId <- c(analysisId, 915)
covariateIds <- c(covariateIds, "")
}
if(useDistinctMeasurementCountShortTerm){
label <- c(label, "DistinctMeasurementCountShortTerm")
analysisId <- c(analysisId, 916)
covariateIds <- c(covariateIds, "")
}
if(useDistinctObservationCountLongTerm){
label <- c(label, "DistinctObservationCountLongTerm")
analysisId <- c(analysisId, 917)
covariateIds <- c(covariateIds, "")
}
if(useDistinctObservationCountMediumTerm){
label <- c(label, "DistinctObservationCountMediumTerm")
analysisId <- c(analysisId, 918)
covariateIds <- c(covariateIds, "")
}
if(useDistinctObservationCountShortTerm){
label <- c(label, "DistinctObservationCountShortTerm")
analysisId <- c(analysisId, 919)
covariateIds <- c(covariateIds, "")
}
if(useVisitCountLongTerm){
label <- c(label, "VisitCountLongTerm")
analysisId <- c(analysisId, 920)
covariateIds <- c(covariateIds, "")
}
if(useVisitCountMediumTerm){
label <- c(label, "VisitCountMediumTerm")
analysisId <- c(analysisId, 921)
covariateIds <- c(covariateIds, "")
}
if(useVisitCountShortTerm){
label <- c(label, "VisitCountShortTerm")
analysisId <- c(analysisId, 922)
covariateIds <- c(covariateIds, "")
}
if(useVisitConceptCountLongTerm){
label <- c(label, "VisitConceptCountLongTerm")
analysisId <- c(analysisId, 923)
covariateIds <- c(covariateIds, "")
}
if(useVisitConceptCountMediumTerm){
label <- c(label, "VisitConceptCountMediumTerm")
analysisId <- c(analysisId, 924)
covariateIds <- c(covariateIds, "")
}
if(useVisitConceptCountShortTerm){
label <- c(label, "VisitConceptCountShortTerm")
analysisId <- c(analysisId, 925)
covariateIds <- c(covariateIds, "")
}
tableSpec <- data.frame(label = label,
analysisId = analysisId,
covariateIds = covariateIds,
stringsAsFactors = F)
result <- list(tableSpec = tableSpec, covariateSetting = covariateSetting)
class(result) <- "tableSpecification"
return(result)
}
#' Create a table 1
#'
#' @description
#' Creates a formatted table of cohort characteristics, to be included in publications or reports.
#' Allows for creating a table describing a single cohort, or a table comparing two cohorts.
#'
#' @param covariateData1 The covariate data of the cohort to be included in the table.
#' @param covariateData2 The covariate data of the cohort to also be included, when comparing two
#' cohorts.
#' @param specifications Specifications of which covariates to display, and how.
#' @param output The output format for the table. Options are \code{output = "two columns"},
#' \code{output = "one column"}, or \code{output = "list"}.
#' @param showCounts Show the number of cohort entries having the binary covariate?
#' @param showPercent Show the percentage of cohort entries having the binary covariate?
#' @param percentDigits Number of digits to be used for percentages.
#' @param stdDiffDigits Number of digits to be used for the standardized differences.
#' @param valueDigits Number of digits to be used for the values of continuous variables.
#'
#' @return
#' A data frame, or, when \code{output = "list"} a list of two data frames.
#'
createTable1 <- function(covariateData1,
covariateData2 = NULL,
specifications = getDefaultTable1Specifications(),
output = "two columns",
showCounts = FALSE,
showPercent = TRUE,
percentDigits = 1,
valueDigits = 1,
stdDiffDigits = 2) {
comparison <- !is.null(covariateData2)
if (!is(covariateData1, "covariateData")) {
stop("covariateData1 is not of type 'covariateData'")
}
if (comparison && !is(covariateData2, "covariateData")) {
stop("covariateData2 is not of type 'covariateData'")
}
if (is.null(covariateData1$covariatesContinuous) && is.null(covariateData1$covariates$averageValue)) {
stop("Covariate1 data is not aggregated")
}
if (comparison && is.null(covariateData2$covariatesContinuous) && is.null(covariateData2$covariates$averageValue)) {
stop("Covariate2 data is not aggregated")
}
if (!showCounts && !showPercent) {
stop("Must show counts or percent, or both")
}
fixCase <- function(label) {
idx <- (toupper(label) == label)
if (any(idx)) {
label[idx] <- paste0(substr(label[idx], 1, 1),
tolower(substr(label[idx], 2, nchar(label[idx]))))
}
return(label)
}
formatCount <- function(x) {
result <- format(round(x), justify = "right", big.mark = ",")
result <- gsub("NA", "", result)
result <- gsub(" ", " ", result)
return(result)
}
formatPercent <- function(x) {
result <- format(round(100*x, percentDigits), digits = percentDigits + 1, justify = "right")
result <- gsub("NA", "", result)
result <- gsub(" ", " ", result)
return(result)
}
formatStdDiff <- function(x) {
result <- format(round(x, stdDiffDigits), digits = stdDiffDigits + 1, justify = "right")
result <- gsub("NA", "", result)
result <- gsub(" ", " ", result)
return(result)
}
formatValue <- function(x) {
return(format(round(x, valueDigits), nsmall = valueDigits))
}
if (is.null(covariateData1$covariates)) {
covariates <- NULL
} else {
covariates <- as.data.frame(ff::as.ram(covariateData1$covariates[, c("covariateId", "sumValue", "averageValue")]))
colnames(covariates) <- c("covariateId", "count1", "percent1")
covariates$count1 <- formatCount(covariates$count1)
covariates$percent1 <- formatPercent(covariates$percent1)
}
if (is.null(covariateData1$covariatesContinuous)) {
covariatesContinuous <- NULL
} else {
covariatesContinuous <- as.data.frame(ff::as.ram(covariateData1$covariatesContinuous[, c("covariateId",
"averageValue",
"standardDeviation",
"minValue",
"p25Value",
"medianValue",
"p75Value",
"maxValue")]))
colnames(covariatesContinuous) <- c("covariateId",
"averageValue1",
"standardDeviation1",
"minValue1",
"p25Value1",
"medianValue1",
"p75Value1",
"maxValue1")
covariatesContinuous$averageValue1 <- formatValue(covariatesContinuous$averageValue1)
covariatesContinuous$standardDeviation1 <- formatValue(covariatesContinuous$standardDeviation1)
covariatesContinuous$minValue1 <- formatValue(covariatesContinuous$minValue1)
covariatesContinuous$p25Value1 <- formatValue(covariatesContinuous$p25Value1)
covariatesContinuous$medianValue1 <- formatValue(covariatesContinuous$medianValue1)
covariatesContinuous$p75Value1 <- formatValue(covariatesContinuous$p75Value1)
covariatesContinuous$maxValue1 <- formatValue(covariatesContinuous$maxValue1)
}
covariateRef <- ff::as.ram(covariateData1$covariateRef)
analysisRef <- ff::as.ram(covariateData1$analysisRef)
if (comparison) {
stdDiff <- FeatureExtraction::computeStandardizedDifference(covariateData1, covariateData2)
if (!is.null(covariateData1$covariates) && !is.null(covariateData2$covariates)) {
tempCovariates <- ff::as.ram(covariateData2$covariates[, c("covariateId", "sumValue", "averageValue")])
colnames(tempCovariates) <- c("covariateId", "count2", "percent2")
tempCovariates$count2 <- formatCount(tempCovariates$count2)
tempCovariates$percent2 <- formatPercent(tempCovariates$percent2)
covariates <- merge(covariates, tempCovariates, all = TRUE)
covariates$count1[is.na(covariates$count1)] <- " 0"
covariates$count2[is.na(covariates$count2)] <- " 0"
covariates$percent1[is.na(covariates$percent1)] <- " 0"
covariates$percent2[is.na(covariates$percent2)] <- " 0"
covariates <- merge(covariates, stdDiff[, c("covariateId", "stdDiff")])
covariates$stdDiff <- formatStdDiff(covariates$stdDiff)
}
if (!is.null(covariatesContinuous)) {
tempCovariates <- as.data.frame(ff::as.ram(covariateData2$covariatesContinuous[, c("covariateId",
"averageValue",
"standardDeviation",
"minValue",
"p25Value",
"medianValue",
"p75Value",
"maxValue")]))
colnames(tempCovariates) <- c("covariateId",
"averageValue2",
"standardDeviation2",
"minValue2",
"p25Value2",
"medianValue2",
"p75Value2",
"maxValue2")
tempCovariates$averageValue2 <- formatValue(tempCovariates$averageValue2)
tempCovariates$standardDeviation2 <- formatValue(tempCovariates$standardDeviation2)
tempCovariates$minValue2 <- formatValue(tempCovariates$minValue2)
tempCovariates$p25Value2 <- formatValue(tempCovariates$p25Value2)
tempCovariates$medianValue2 <- formatValue(tempCovariates$medianValue2)
tempCovariates$p75Value2 <- formatValue(tempCovariates$p75Value2)
tempCovariates$maxValue2 <- formatValue(tempCovariates$maxValue2)
covariatesContinuous <- merge(covariatesContinuous, tempCovariates, all = TRUE)
covariatesContinuous$averageValue1[is.na(covariatesContinuous$averageValue1)] <- " "
covariatesContinuous$standardDeviation1[is.na(covariatesContinuous$standardDeviation1)] <- " "
covariatesContinuous$minValue1[is.na(covariatesContinuous$minValue1)] <- " "
covariatesContinuous$p25Value1[is.na(covariatesContinuous$p25Value1)] <- " "
covariatesContinuous$medianValue1[is.na(covariatesContinuous$medianValue1)] <- " "
covariatesContinuous$p75Value1[is.na(covariatesContinuous$p75Value1)] <- " "
covariatesContinuous$maxValue1[is.na(covariatesContinuous$maxValue1)] <- " "
covariatesContinuous$averageValue2[is.na(covariatesContinuous$averageValue2)] <- " "
covariatesContinuous$standardDeviation2[is.na(covariatesContinuous$standardDeviation2)] <- " "
covariatesContinuous$minValue2[is.na(covariatesContinuous$minValue2)] <- " "
covariatesContinuous$p25Value2[is.na(covariatesContinuous$p25Value2)] <- " "
covariatesContinuous$medianValue2[is.na(covariatesContinuous$medianValue2)] <- " "
covariatesContinuous$p75Value2[is.na(covariatesContinuous$p75Value2)] <- " "
covariatesContinuous$maxValue2[is.na(covariatesContinuous$maxValue2)] <- " "
covariatesContinuous <- merge(covariatesContinuous, stdDiff[, c("covariateId", "stdDiff")])
covariatesContinuous$stdDiff <- formatStdDiff(covariatesContinuous$stdDiff)
}
idx <- !ffbase::`%in%`(covariateData2$covariateRef$covariateId,
covariateData1$covariateRef$covariateId)
if (ffbase::any.ff(idx)) {
covariateRef <- rbind(covariateRef, ff::as.ram(covariateData2$covariateRef[idx, ]))
}
} else {
covariates$count2 <- " 0"
covariates$percent2 <- " 0"
covariates$stdDiff <- " 0"
covariatesContinuous$averageValue2 <- " "
covariatesContinuous$standardDeviation2 <- " "
covariatesContinuous$minValue2 <- " "
covariatesContinuous$p25Value2 <- " "
covariatesContinuous$medianValue2 <- " "
covariatesContinuous$p75Value2 <- " "
covariatesContinuous$maxValue2 <- " "
covariatesContinuous$stdDiff <- " "
}
binaryTable <- data.frame()
continuousTable <- data.frame()
for (i in 1:nrow(specifications)) {
if (specifications$analysisId[i] == "") {
binaryTable <- rbind(binaryTable,
data.frame(Characteristic = specifications$label[i], value = ""))
} else {
idx <- analysisRef$analysisId == specifications$analysisId[i]
if (any(idx)) {
isBinary <- analysisRef$isBinary[idx]
covariateIds <- NULL
if (isBinary == "Y") {
# Binary
if (specifications$covariateIds[i] == "") {
idx <- covariateRef$analysisId == specifications$analysisId[i]
} else {
covariateIds <- as.numeric(strsplit(specifications$covariateIds[i], ",")[[1]])
idx <- covariateRef$covariateId %in% covariateIds
}
if (any(idx)) {
covariateRefSubset <- covariateRef[idx, ]
covariatesSubset <- merge(covariates, covariateRefSubset)
if (is.null(covariateIds)) {
covariatesSubset <- covariatesSubset[order(covariatesSubset$covariateId), ]
} else {
covariatesSubset <- merge(covariatesSubset, data.frame(covariateId = covariateIds,
rn = 1:length(covariateIds)))
covariatesSubset <- covariatesSubset[order(covariatesSubset$rn,
covariatesSubset$covariateId), ]
}
covariatesSubset$covariateName <- fixCase(gsub("^.*: ",
"",
covariatesSubset$covariateName))
if (specifications$covariateIds[i] == "" || length(covariateIds) > 1) {
binaryTable <- rbind(binaryTable, data.frame(Characteristic = specifications$label[i],
count1 = "",
percent1 = "",
count2 = "",
percent2 = "",
stdDiff = "",
stringsAsFactors = FALSE))
binaryTable <- rbind(binaryTable,
data.frame(Characteristic = paste0(" ", covariatesSubset$covariateName),
count1 = covariatesSubset$count1,
percent1 = covariatesSubset$percent1,
count2 = covariatesSubset$count2,
percent2 = covariatesSubset$percent2,
stdDiff = covariatesSubset$stdDiff,
stringsAsFactors = FALSE))
} else {
binaryTable <- rbind(binaryTable, data.frame(Characteristic = specifications$label[i],
count1 = covariatesSubset$count1,
percent1 = covariatesSubset$percent1,
count2 = covariatesSubset$count2,
percent2 = covariatesSubset$percent2,
stdDiff = covariatesSubset$stdDiff,
stringsAsFactors = FALSE))
}
}
} else {
# Not binary
if (specifications$covariateIds[i] == "") {
idx <- covariateRef$analysisId == specifications$analysisId[i]
} else {
covariateIds <- as.numeric(strsplit(specifications$covariateIds[i], ",")[[1]])
idx <- covariateRef$covariateId %in% covariateIds
}
if (any(idx)) {
covariateRefSubset <- covariateRef[idx, ]
covariatesSubset <- covariatesContinuous[covariatesContinuous$covariateId %in% covariateRefSubset$covariateId, ]
covariatesSubset <- merge(covariatesSubset, covariateRefSubset)
if (is.null(covariateIds)) {
covariatesSubset <- covariatesSubset[order(covariatesSubset$covariateId), ]
} else {
covariatesSubset <- merge(covariatesSubset, data.frame(covariateId = covariateIds,
rn = 1:length(covariateIds)))
covariatesSubset <- covariatesSubset[order(covariatesSubset$rn,
covariatesSubset$covariateId), ]
}
covariatesSubset$covariateName <- fixCase(gsub("^.*: ",
"",
covariatesSubset$covariateName))
if (specifications$covariateIds[i] == "" || length(covariateIds) > 1) {
continuousTable <- rbind(continuousTable,
data.frame(Characteristic = specifications$label[i],
value1 = "",
value2 = "",
stdDiff = "",
stringsAsFactors = FALSE))
for (j in 1:nrow(covariatesSubset)) {
continuousTable <- rbind(continuousTable,
data.frame(Characteristic = paste0(" ", covariatesSubset$covariateName[j]),
value1 = "",
value2 = "",
stdDiff = "",
stringsAsFactors = FALSE))
continuousTable <- rbind(continuousTable, data.frame(Characteristic = c(" Mean",
" Std. deviation",
" Minimum",
" 25th percentile",
" Median",
" 75th percentile",
" Maximum"),
value1 = c(covariatesSubset$averageValue1[j],
covariatesSubset$standardDeviation1[j],
covariatesSubset$minValue1[j],
covariatesSubset$p25Value1[j],
covariatesSubset$medianValue1[j],
covariatesSubset$p75Value1[j],
covariatesSubset$maxValue1[j]),
value2 = c(covariatesSubset$averageValue2[j],
covariatesSubset$standardDeviation2[j],
covariatesSubset$minValue2[j],
covariatesSubset$p25Value2[j],
covariatesSubset$medianValue2[j],
covariatesSubset$p75Value2[j],
covariatesSubset$maxValue2[j]),
stdDiff = c(covariatesSubset$stdDiff[j],
" ",
" ",
" ",
" ",
" ",
" "),
stringsAsFactors = FALSE))
}
} else {
continuousTable <- rbind(continuousTable,
data.frame(Characteristic = specifications$label[i],
value1 = "",
value2 = "",
stdDiff = "",
stringsAsFactors = FALSE))
continuousTable <- rbind(continuousTable, data.frame(Characteristic = c(" Mean",
" Std. deviation",
" Minimum",
" 25th percentile",
" Median",
" 75th percentile",
" Maximum"),
value1 = c(covariatesSubset$averageValue1,
covariatesSubset$standardDeviation1,
covariatesSubset$minValue1,
covariatesSubset$p25Value1,
covariatesSubset$medianValue1,
covariatesSubset$p75Value1,
covariatesSubset$maxValue1),
value2 = c(covariatesSubset$averageValue2,
covariatesSubset$standardDeviation2,
covariatesSubset$minValue2,
covariatesSubset$p25Value2,
covariatesSubset$medianValue2,
covariatesSubset$p75Value2,
covariatesSubset$maxValue2),
stdDiff = c(covariatesSubset$stdDiff,
" ",
" ",
" ",
" ",
" ",
" "),
stringsAsFactors = FALSE))
}
}
}
}
}
}
if (nrow(continuousTable) != 0) {
if (showCounts && showPercent) {
if (comparison) {
continuousTable$dummy1 <- ""
continuousTable$dummy2 <- ""
continuousTable <- continuousTable[, c(1, 5, 2, 6, 3, 4)]
colnames(continuousTable) <- c("Characteristic", "", "Value", "", "Value", "Std.Diff")
} else {
continuousTable$dummy <- ""
continuousTable <- continuousTable[, c(1,3,2)]
colnames(continuousTable) <- c("Characteristic", "", "Value")
}
} else {
if (comparison) {
colnames(continuousTable) <- c("Characteristic", "Value", "Value", "Std.Diff")
} else {
continuousTable$value2 <- NULL
continuousTable$stdDiff <- NULL
colnames(continuousTable) <- c("Characteristic", "Value")
}
}
}
if (nrow(binaryTable) != 0) {
if (comparison) {
colnames(binaryTable) <- c("Characteristic",
"Count",
paste0("% (n = ",
formatCount(covariateData1$metaData$populationSize),
")"),
"Count",
paste0("% (n = ",
formatCount(covariateData2$metaData$populationSize),
")"),
"Std.Diff")
if (!showCounts) {
binaryTable[, 4] <- NULL
binaryTable[, 2] <- NULL
}
if (!showPercent) {
binaryTable[, 5] <- NULL
binaryTable[, 3] <- NULL
}
} else {
binaryTable$count2 <- NULL
binaryTable$percent2 <- NULL
binaryTable$stdDiff <- NULL
colnames(binaryTable) <- c("Characteristic",
"Count",
paste0("% (n = ",
formatCount(covariateData1$metaData$populationSize),
")"))
if (!showCounts) {
binaryTable[, 2] <- NULL
}
if (!showPercent) {
binaryTable[, 3] <- NULL
}
}
}
if (output == "two columns") {
if (nrow(binaryTable) > nrow(continuousTable)) {
if (nrow(continuousTable) > 0) {
rowsPerColumn <- ceiling((nrow(binaryTable) + nrow(continuousTable) + 2)/2)
column1 <- binaryTable[1:rowsPerColumn, ]
ct <- continuousTable
colnames(ct) <- colnames(binaryTable)
column2 <- rbind(binaryTable[(rowsPerColumn + 1):nrow(binaryTable),
],
rep("", ncol(binaryTable)),
colnames(continuousTable),
ct)
} else {
rowsPerColumn <- ceiling((nrow(binaryTable) + nrow(continuousTable))/2)
column1 <- binaryTable[1:rowsPerColumn, ]
column2 <- binaryTable[(rowsPerColumn + 1):nrow(binaryTable), ]
}
if (nrow(column1) > nrow(column2)) {
column2 <- rbind(column2, rep("", ncol(binaryTable)))
}
result <- cbind(column1, column2)
} else {
stop("Don't know what to do when there are more rows in the table of continuous covariates than there are in the table of binary covariates.")
}
} else if (output == "one column") {
ct <- continuousTable
colnames(ct) <- colnames(binaryTable)
result <- rbind(binaryTable,
rep("", ncol(binaryTable)),
colnames(continuousTable),
ct)
} else {
result <- list(part1 = binaryTable, part2 = continuousTable)
}
return(result)
}
chandryou/TicagrelorVsClopidogrel documentation built on Oct. 9, 2020, 6:22 a.m.
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Defines functions createTable1 setTableSpecification mapCovariates comparativeCharacterization additionalResult
Documented in additionalResult
# Copyright 2020 Observational Health Data Sciences and Informatics
#
# This file is part of TicagrelorVsClopidogrel
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#' Generate result for revision
#'
#' @details
#' Generate result for revision
#'
#' The \code{createCohorts}, \code{synthesizePositiveControls}, \code{runAnalyses}, and \code{runDiagnostics} arguments
#' are intended to be used to run parts of the full study at a time, but none of the parts are considerd to be optional.
#'
#' @param connectionDetails An object of type \code{connectionDetails} as created using the
#' \code{\link[DatabaseConnector]{createConnectionDetails}} function in the
#' DatabaseConnector package.
#' @param cdmDatabaseSchema Schema name where your patient-level data in OMOP CDM format resides.
#' Note that for SQL Server, this should include both the database and
#' schema name, for example 'cdm_data.dbo'.
#' @param cohortDatabaseSchema Schema name where intermediate data can be stored. You will need to have
#' write priviliges in this schema. Note that for SQL Server, this should
#' include both the database and schema name, for example 'cdm_data.dbo'.
#' @param cohortTable The name of the table that will be created in the work database schema.
#' This table will hold the exposure and outcome cohorts used in this
#' study.
#' @param oracleTempSchema Should be used in Oracle to specify a schema where the user has write
#' priviliges for storing temporary tables.
#' @param outputFolder Name of local folder to place results; make sure to use forward slashes
#' (/). Do not use a folder on a network drive since this greatly impacts
#' performance.
#' @param databaseId A short string for identifying the database (e.g.
#' 'Synpuf').
#' @param minCellCount The minimum number of subjects contributing to a count before it can be included
#' in packaged results.
#'
#' @examples
#' \dontrun{
#' connectionDetails <- createConnectionDetails(dbms = "postgresql",
#' user = "joe",
#' password = "secret",
#' server = "myserver")
#'
#' execute(connectionDetails,
#' cdmDatabaseSchema = "cdm_data",
#' cohortDatabaseSchema = "study_results",
#' cohortTable = "cohort",
#' oracleTempSchema = NULL,
#' outputFolder = "c:/temp/study_results",
#' maxCores = 4)
#' }
#'
# Generation additional table 1
#' @export
additionalResult <- function(connectionDetails = connectionDetails,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
oracleTempSchema = oracleTempSchema,
outputFolder = outputFolder,
databaseId = databaseId,
minCellCount = 1){
start <- Sys.time()
exportFolder <- file.path(outputFolder, "export")
if (!file.exists(exportFolder)) {
dir.create(exportFolder, recursive = TRUE)
}
####Cox assumption test####
popList <- list.files(file.path(outputFolder,"cmOutput"), pattern = "^StratPop_l1_s1_p1.*s1_o.*.rds")
for(i in 1:length(popList)){
if (i==1) {coxTable <- data.frame()}
popName <- popList[i]
pop <- readRDS(file.path(outputFolder,"cmOutput",popName))
exportName <- gsub("\\.rds","", gsub("StratPop_l1_s1_p1_","",popName))
if(sum(pop$outcomeCount)!=0){
try({
fit <- survival::coxph(survival::Surv(survivalTime, outcomeCount)~treatment, data = pop)
coxTest <- survival::cox.zph(fit)
coxTable1 <- as.data.frame(coxTest$table)
coxTable1$name <- exportName
coxTable <- rbind(coxTable,coxTable1)
#plotZph <- survminer::ggcoxzph(coxTest)
#if(min(coxTable1$p, na.rm = T)<0.05) ggplot2::ggsave(file.path(outputFolder,"export",paste0(exportName,"_graph.pdf" )),print(plotZph))
})
}
if (i == length(popList)) write.csv(coxTable, file.path(exportFolder,"rev_cox_assumption.csv" ))
}
####Baseline characteristics####
primaryPop <- readRDS(file.path(outputFolder, "cmOutput", "StratPop_l1_s1_p1_t874_c929_s1_o1240.rds"))
numAtRisk <- data.frame(c90=sum(primaryPop[primaryPop$survivalTime>=90,]$treatment ==0),
t90=sum(primaryPop[primaryPop$survivalTime>=90,]$treatment ==1),
c180=sum(primaryPop[primaryPop$survivalTime>=180,]$treatment ==0),
t180=sum(primaryPop[primaryPop$survivalTime>=180,]$treatment ==1),
c270=sum(primaryPop[primaryPop$survivalTime>=270,]$treatment ==0),
t270=sum(primaryPop[primaryPop$survivalTime>=270,]$treatment ==1),
c360=sum(primaryPop[primaryPop$survivalTime>=360,]$treatment ==0),
t360=sum(primaryPop[primaryPop$survivalTime>=360,]$treatment ==1))
write.csv(numAtRisk, file.path(exportFolder, "rev_number_at_risk.csv"))
popList <- list.files(file.path(outputFolder,"cmOutput"), pattern = "StratPop_l1_s1_p1_t874_c929_s1_o1240.rds|StudyPop_l1_s1_t874_c929_o1240.rds")
connectionDetails$schema <- cohortDatabaseSchema
connection <- DatabaseConnector::connect(connectionDetails)
for(i in 1:length(popList)){
if (i==1){
targetIds <- c()
comparatorIds <- c()
}
popName <- popList[i]
exportName <- gsub("\\.rds","", gsub("Pop_l1_s1_","",popName))
origTargetId <- 874
origComparatorId <- 929
outcomeId <- 1240
pop <- readRDS(file.path(outputFolder,"cmOutput", popName))
pop$cohortId <- NA
targetId <- as.numeric(sprintf("%d%04d",origTargetId,outcomeId))
comparatorId <- as.numeric(sprintf("%d%04d",origComparatorId,outcomeId))
pop$cohortId[pop$treatment==1] <- targetId
pop$cohortId[pop$treatment==0] <- comparatorId
popCohortTable <- data.frame(cohort_definition_id = pop$cohortId,
subject_id = pop$subjectId,
cohort_start_date = pop$cohortStartDate,
cohort_end_date = pop$cohortStartDate)
# Delete cohort with same cohort ID
sql <- SqlRender::loadRenderTranslateSql(sqlFilename = "DeleteCohort.sql",
packageName = "TicagrelorVsClopidogrel",
dbms = attr(connection, "dbms"),
oracleTempSchema = oracleTempSchema,
target_database_schema = cohortDatabaseSchema,
target_cohort_table = cohortTable,
target_cohort_ids = paste0(targetId, comparatorId, collapse = ","))
DatabaseConnector::executeSql(connection, sql, progressBar = FALSE, reportOverallTime = FALSE)
DatabaseConnector::insertTable(connection = connection,
tableName = cohortTable,
data = popCohortTable,
dropTableIfExists = F,
createTable = F)
targetIds <- c(targetIds, targetId)
comparatorIds <- c(comparatorIds, comparatorId)
}
DatabaseConnector::disconnect(connection)
targetName = "ticagrelor"
comparatorName = "clopidogrel"
# exportFolder <- file.path(outputFolder, "export")
# #Defining concept IDs
conditionGroupConceptIds <-
c(320128,201254,201826,432867,317309,319835,4232697,192359) #102
shorTermAcs <- c(315296, 444406, 438170, 434376, 312327) #104
drugGroupConceptIds <- c(19047423,19017067,1310149,43013024,36428260,40228152,21601784,21601823,21601665,21601744,21601461,21601855,21600095,21600713,21600744) #412
deviceConceptIds <- c(45772824) #604
#measConceptIds <- c(3038553000,3004249000,3012888000,3000963713,3004501840,3008631840,3048150842) #708
measValConceptIds <- c(3038553000,3004249000,3012888000,3000963713,3004501840,3008631840,3048150842)
for( i in 1:length(targetIds)){
targetCohortId <- targetIds[i]
comparatorCohortId <- comparatorIds[i]
targetCohortName = "ticagrelor"
comparatorCohortName= "clopidogrel"
for(endDay in c(0)){
tableSpecification <- setTableSpecification(useDemographicsGender = T,
useDemographicsAge = T,
useDemographicsAgeGroup = T,
useDemographicsRace = T,
useDemographicsEthnicity = F,
useDemographicsIndexYear = T,
useDemographicsIndexMonth = F,
useDemographicsPriorObservationTime = FALSE,
useDemographicsPostObservationTime = FALSE,
useDemographicsTimeInCohort = FALSE,
useDemographicsIndexYearMonth = F,
conceptIdsConditionOccurrenceAnyTimePrior = c(),
conceptIdsConditionOccurrenceLongTerm = conditionGroupConceptIds,
conceptIdsConditionOccurrenceMediumTerm = c(),
conceptIdsConditionOccurrenceShortTerm = shorTermAcs,
conceptIdsConditionOccurrencePrimaryInpatientAnyTimePrior = c(),
conceptIdsConditionOccurrencePrimaryInpatientLongTerm = c(),
conceptIdsConditionOccurrencePrimaryInpatientMediumTerm = c(),
conceptIdsConditionOccurrencePrimaryInpatientShortTerm = c(),
conceptIdsConditionEraAnyTimePrior = c(),
conceptIdsConditionEraLongTerm = c(),
conceptIdsConditionEraMediumTerm = c(),
conceptIdsConditionEraShortTerm = c(),
conceptIdsConditionEraOverlapping = c(),
conceptIdsConditionEraStartLongTerm = c(),
conceptIdsConditionEraStartMediumTerm = c(),
conceptIdsConditionEraStartShortTerm = c(),
conceptIdsConditionGroupEraAnyTimePrior = c(),
conceptIdsConditionGroupEraLongTerm = c(),
conceptIdsConditionGroupEraMediumTerm = c(),
conceptIdsConditionGroupEraShortTerm = shorTermAcs,
conceptIdsConditionGroupEraOverlapping = c(),
conceptIdsConditionGroupEraStartLongTerm = c(),
conceptIdsConditionGroupEraStartMediumTerm = c(),
conceptIdsConditionGroupEraStartShortTerm = c(),
conceptIdsDrugExposureAnyTimePrior = c(),
conceptIdsDrugExposureLongTerm = c(),
conceptIdsDrugExposureMediumTerm = c(),
conceptIdsDrugExposureShortTerm = c(),
conceptIdsDrugEraAnyTimePrior = c(),
conceptIdsDrugEraLongTerm = c(),
conceptIdsDrugEraMediumTerm = c(),
conceptIdsDrugEraShortTerm = c(),
conceptIdsDrugEraOverlapping = c(),
conceptIdsDrugEraStartLongTerm = c(),
conceptIdsDrugEraStartMediumTerm = c(),
conceptIdsDrugEraStartShortTerm = c(),
conceptIdsDrugGroupEraAnyTimePrior = c(),
conceptIdsDrugGroupEraLongTerm = c(),
conceptIdsDrugGroupEraMediumTerm = c(),
conceptIdsDrugGroupEraShortTerm = c(),
conceptIdsDrugGroupEraOverlapping = c(),
conceptIdsDrugGroupEraStartLongTerm = c(),
conceptIdsDrugGroupEraStartMediumTerm = c(),
conceptIdsDrugGroupEraStartShortTerm = c(),
conceptIdsProcedureOccurrenceAnyTimePrior = c(),
conceptIdsProcedureOccurrenceLongTerm = c(),
conceptIdsProcedureOccurrenceMediumTerm = c(),
conceptIdsProcedureOccurrenceShortTerm = c(),
conceptIdsDeviceExposureAnyTimePrior = c(),
conceptIdsDeviceExposureLongTerm = c(),
conceptIdsDeviceExposureMediumTerm = c(),
conceptIdsDeviceExposureShortTerm = c(),
conceptIdsMeasurementAnyTimePrior = c(),
conceptIdsMeasurementLongTerm = c(),
conceptIdsMeasurementMediumTerm = c(),
conceptIdsMeasurementShortTerm = c(),#measConceptIds,
conceptIdsMeasurementValueAnyTimePrior = c(),
conceptIdsMeasurementValueLongTerm = c(),
conceptIdsMeasurementValueMediumTerm = c(),
conceptIdsMeasurementValueShortTerm = measValConceptIds, #measConceptIds,
conceptIdsMeasurementRangeGroupAnyTimePrior = c(),
conceptIdsMeasurementRangeGroupLongTerm = c(),
conceptIdsMeasurementRangeGroupMediumTerm = c(),
conceptIdsMeasurementRangeGroupShortTerm = c(),
conceptIdsObservationAnyTimePrior = c(),
conceptIdsObservationLongTerm = c(),
conceptIdsObservationMediumTerm = c(),
conceptIdsObservationShortTerm = c(),
useCharlsonIndex = F,
useDcsi = FALSE,
useChads2 = FALSE,
useChads2Vasc = FALSE,
useHfrs = F,#T,
useDistinctConditionCountLongTerm = FALSE,
useDistinctConditionCountMediumTerm = FALSE,
useDistinctConditionCountShortTerm = FALSE,
useDistinctIngredientCountLongTerm = FALSE,
useDistinctIngredientCountMediumTerm = FALSE,
useDistinctIngredientCountShortTerm = FALSE,
useDistinctProcedureCountLongTerm = FALSE,
useDistinctProcedureCountMediumTerm = FALSE,
useDistinctProcedureCountShortTerm = FALSE,
useDistinctMeasurementCountLongTerm = FALSE,
useDistinctMeasurementCountMediumTerm = FALSE,
useDistinctMeasurementCountShortTerm = FALSE,
useDistinctObservationCountLongTerm = FALSE,
useDistinctObservationCountMediumTerm = FALSE,
useDistinctObservationCountShortTerm = FALSE,
useVisitCountLongTerm = F,
useVisitCountMediumTerm = F,
useVisitCountShortTerm = F,
useVisitConceptCountLongTerm = F,
useVisitConceptCountMediumTerm = F,
useVisitConceptCountShortTerm = F,
longTermStartDays = -365,
mediumTermStartDays = -30,
shortTermStartDays = -7,
endDays = endDay) #you can try diverse time settings
tryCatch({
comparativeCharacterization(connectionDetails = connectionDetails,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
oracleTempSchema = oracleTempSchema,
outputFolder = outputFolder,
minCellCount = minCellCount,
targetCohortId = targetCohortId,
comparatorCohortId = comparatorCohortId,#7,
outcomeCohortIds = NULL,
tableSpecification = tableSpecification,
sampleSize = NULL,
output = "one column",
percentDigits = 1,
valueDigits = 1,
stdDiffDigits = 2,
studyPopulationSetting = NULL,
fileName = file.path(exportFolder, sprintf("rev_base_char_t%s_c%s.csv",targetCohortId, comparatorCohortId)))
},
error = function(e) {
ParallelLogger::logTrace(paste0(sprintf("Generating table 1 for cohort ID %s_%s is failed. The error message:", targetCohortId, comparatorCohortId), e))},
finally = {
ParallelLogger::logTrace('Done.')})
}
}
# Add all to zip file -------------------------------------------------------------------------------
ParallelLogger::logInfo("Adding results to zip file")
zipName <- file.path(exportFolder, paste0("Results_for_revision", databaseId, ".zip"))
files <- list.files(exportFolder, pattern = "rev.*\\.csv$")
oldWd <- setwd(exportFolder)
on.exit(setwd(oldWd), add = TRUE)
DatabaseConnector::createZipFile(zipFile = zipName, files = files)
ParallelLogger::logInfo("Results are ready for sharing at:", zipName)
delta <- Sys.time() - start
ParallelLogger::logInfo(paste("Generating additional result took",
signif(delta, 3),
attr(delta, "units")))
}
#' Comparative Characterization
#'
#' @details
#' This function create the comparative table 1 for target and comparator
#'
#' @export
comparativeCharacterization <- function(connectionDetails,
cdmDatabaseSchema,
cohortDatabaseSchema = cdmDatabaseSchema,
cohortTable = "cohort",
oracleTempSchema = NULL,
outputFolder,
minCellCount = 0,
targetCohortId,
comparatorCohortId = NULL,
outcomeCohortIds = NULL,
tableSpecification = setTableSpecification(),
sampleSize = NULL,
output = "one column",
percentDigits = 1,
valueDigits = 1,
stdDiffDigits = 2,
studyPopulationSetting = NULL,
fileName = NULL){
if (!file.exists(outputFolder))
dir.create(outputFolder, recursive = TRUE)
if (!is.null(getOption("fftempdir")) && !file.exists(getOption("fftempdir"))) {
warning("fftempdir '", getOption("fftempdir"), "' not found. Attempting to create folder")
dir.create(getOption("fftempdir"), recursive = TRUE)
}
ParallelLogger::addDefaultFileLogger(file.path(outputFolder, "log.txt"))
if(is.null(outcomeCohortIds)){
targetCovData <- FeatureExtraction::getDbCovariateData(connectionDetails = connectionDetails,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
cohortId = targetCohortId,
rowIdField = "subject_id",
covariateSettings = tableSpecification$covariateSetting,
aggregated = F)
targetCovAggData <- FeatureExtraction::aggregateCovariates(targetCovData)
ParallelLogger::logInfo(sprintf("Covariates for target Id %s are extracted", targetCohortId))
if(!is.null(comparatorCohortId)){
comparatorCovData <- FeatureExtraction::getDbCovariateData(connectionDetails = connectionDetails,
cdmDatabaseSchema = cdmDatabaseSchema,
cohortDatabaseSchema = cohortDatabaseSchema,
cohortTable = cohortTable,
cohortId = comparatorCohortId,
rowIdField = "subject_id",
covariateSettings = tableSpecification$covariateSetting,
aggregated = F)
comparatorCovAggData <- FeatureExtraction::aggregateCovariates(comparatorCovData)
ParallelLogger::logInfo(sprintf("Covariates for comparator Id %s are extracted", comparatorCohortId))
}else {
comparatorCovData <- NULL
comparatorCovAggData <- NULL
}
table1 <- createTable1(targetCovAggData,
comparatorCovAggData,
specification = tableSpecification$tableSpec,
output = "one column",
showCounts = TRUE,
showPercent = TRUE,
percentDigits = 1,
valueDigits = 1,
stdDiffDigits = 2)
countNum <- as.numeric(gsub(",","",as.character(table1$Count)))
smallCellIndex <- which(((countNum < minCellCount) & (countNum > 0)) & (!is.na(countNum)))
if(length(smallCellIndex) > 0){
table1[smallCellIndex, 2] <- sprintf("< %d", minCellCount)
table1[smallCellIndex, 3] <- NA
}
if(!is.null(fileName)){
write.csv(table1,fileName)
ParallelLogger::logInfo(sprintf("Table 1 is saved in %s", fileName))
}
# if(!is.null(fileName)){
# write.csv(table1,fileName)
# ParallelLogger::logInfo(sprintf("Table 1 is saved in %s", fileName))
# }
}else{
stop("currently, stratification on outcome Id or incidence calculation is not supported")
}
}
# restricts to pop and saves/creates mapping
mapCovariates <- function(plpData,
population){
covariates = plpData$covariates
covariateRef = plpData$covariateRef
# restrict to population stratified by outcomes
ParallelLogger::logTrace('restricting to population according to the outcome status...')
idx <- ffbase::ffmatch(x = covariates$rowId, table = ff::as.ff(population$rowId))
idx <- ffbase::ffwhich(idx, !is.na(idx))
covariates <- covariates[idx, ]
covariateData = list(covariates = covariates,
covariateRef = covariateRef,
timeRef = plpData$timeRef,
analysisRef = plpData$analysisRef,
metaData = plpData$metaData)
class (covariateData) = "covariateData"
return(covariateData)
}
#' Set the setting for the table 1
#'
#' @details
#' This function create the setting for the table 1.
#'
#' @param useDemographicsGender = FALSE
#' @param useDemographicsAge
#' @param useDemographicsAgeGroup
#' @param useDemographicsRace
#' @param useDemographicsEthnicity
#' @param useDemographicsIndexYear
#' @param useDemographicsIndexMonth
#' @param useDemographicsPriorObservationTime
#' @param useDemographicsPostObservationTime
#' @param useDemographicsTimeInCohort
#' @param useDemographicsIndexYearMonth
#' @param conceptIdsConditionOccurrenceAnyTimePrior
#' @param conceptIdsConditionOccurrenceLongTerm
#' @param conceptIdsConditionOccurrenceMediumTerm
#' @param conceptIdsConditionOccurrenceShortTerm
#' @param conceptIdsConditionOccurrencePrimaryInpatientAnyTimePrior
#' @param conceptIdsConditionOccurrencePrimaryInpatientLongTerm
#' @param conceptIdsConditionOccurrencePrimaryInpatientMediumTerm
#' @param conceptIdsConditionOccurrencePrimaryInpatientShortTerm
#' @param conceptIdsConditionEraAnyTimePrior
#' @param conceptIdsConditionEraLongTerm
#' @param conceptIdsConditionEraMediumTerm
#' @param conceptIdsConditionEraShortTerm
#' @param conceptIdsConditionEraOverlapping
#' @param conceptIdsConditionEraStartLongTerm
#' @param conceptIdsConditionEraStartMediumTerm
#' @param conceptIdsConditionEraStartShortTerm
#' @param conceptIdsConditionGroupEraAnyTimePrior
#' @param conceptIdsConditionGroupEraLongTerm
#' @param conceptIdsConditionGroupEraMediumTerm
#' @param conceptIdsConditionGroupEraShortTerm
#' @param conceptIdsConditionGroupEraOverlapping
#' @param conceptIdsConditionGroupEraStartLongTerm
#' @param conceptIdsConditionGroupEraStartMediumTerm
#' @param conceptIdsConditionGroupEraStartShortTerm
#' @param conceptIdsDrugExposureAnyTimePrior
#' @param conceptIdsDrugExposureLongTerm
#' @param conceptIdsDrugExposureMediumTerm
#' @param conceptIdsDrugExposureShortTerm
#' @param conceptIdsDrugEraAnyTimePrior
#' @param conceptIdsDrugEraLongTerm
#' @param conceptIdsDrugEraMediumTerm
#' @param conceptIdsDrugEraShortTerm
#' @param conceptIdsDrugEraOverlapping
#' @param conceptIdsDrugEraStartLongTerm
#' @param conceptIdsDrugEraStartMediumTerm
#' @param conceptIdsDrugEraStartShortTerm
#' @param conceptIdsDrugGroupEraAnyTimePrior
#' @param conceptIdsDrugGroupEraLongTerm
#' @param conceptIdsDrugGroupEraMediumTerm
#' @param conceptIdsDrugGroupEraShortTerm
#' @param conceptIdsDrugGroupEraOverlapping
#' @param conceptIdsDrugGroupEraStartLongTerm
#' @param conceptIdsDrugGroupEraStartMediumTerm
#' @param conceptIdsDrugGroupEraStartShortTerm
#' @param conceptIdsProcedureOccurrenceAnyTimePrior
#' @param conceptIdsProcedureOccurrenceLongTerm
#' @param conceptIdsProcedureOccurrenceMediumTerm
#' @param conceptIdsProcedureOccurrenceShortTerm
#' @param conceptIdsDeviceExposureAnyTimePrior
#' @param conceptIdsDeviceExposureLongTerm
#' @param conceptIdsDeviceExposureMediumTerm
#' @param conceptIdsDeviceExposureShortTerm
#' @param conceptIdsMeasurementAnyTimePrior
#' @param conceptIdsMeasurementLongTerm
#' @param conceptIdsMeasurementMediumTerm
#' @param conceptIdsMeasurementShortTerm
#' @param conceptIdsMeasurementValueAnyTimePrior
#' @param conceptIdsMeasurementValueLongTerm
#' @param conceptIdsMeasurementValueMediumTerm
#' @param conceptIdsMeasurementValueShortTerm
#' @param conceptIdsMeasurementRangeGroupAnyTimePrior
#' @param conceptIdsMeasurementRangeGroupLongTerm
#' @param conceptIdsMeasurementRangeGroupMediumTerm
#' @param conceptIdsMeasurementRangeGroupShortTerm
#' @param conceptIdsObservationAnyTimePrior
#' @param conceptIdsObservationLongTerm
#' @param conceptIdsObservationMediumTerm
#' @param conceptIdsObservationShortTerm
#' @param useCharlsonIndex
#' @param useDcsi
#' @param useChads2
#' @param useChads2Vasc
#' @param useHfrs
#' @param useDistinctConditionCountLongTerm
#' @param useDistinctConditionCountMediumTerm
#' @param useDistinctConditionCountShortTerm
#' @param useDistinctIngredientCountLongTerm
#' @param useDistinctIngredientCountMediumTerm
#' @param useDistinctIngredientCountShortTerm
#' @param useDistinctProcedureCountLongTerm
#' @param useDistinctProcedureCountMediumTerm
#' @param useDistinctProcedureCountShortTerm
#' @param useDistinctMeasurementCountLongTerm
#' @param useDistinctMeasurementCountMediumTerm
#' @param useDistinctMeasurementCountShortTerm
#' @param useDistinctObservationCountLongTerm
#' @param useDistinctObservationCountMediumTerm
#' @param useDistinctObservationCountShortTerm
#' @param useVisitCountLongTerm
#' @param useVisitCountMediumTerm
#' @param useVisitCountShortTerm
#' @param useVisitConceptCountLongTerm
#' @param useVisitConceptCountMediumTerm
#' @param useVisitConceptCountShortTerm
#' @param longTermStartDays
#' @param mediumTermStartDays
#' @param shortTermStartDays
#' @param endDays
#'
#' @return
#' An object of type \code{tableSpecification}, to be used in other functions.
#'
#' @export
setTableSpecification <- function(useDemographicsGender = FALSE,
useDemographicsAge = FALSE,
useDemographicsAgeGroup = FALSE,
useDemographicsRace = FALSE,
useDemographicsEthnicity = FALSE,
useDemographicsIndexYear = FALSE,
useDemographicsIndexMonth = FALSE,
useDemographicsPriorObservationTime = FALSE,
useDemographicsPostObservationTime = FALSE,
useDemographicsTimeInCohort = FALSE,
useDemographicsIndexYearMonth = FALSE,
conceptIdsConditionOccurrenceAnyTimePrior = c(),
conceptIdsConditionOccurrenceLongTerm = c(),
conceptIdsConditionOccurrenceMediumTerm = c(),
conceptIdsConditionOccurrenceShortTerm = c(),
conceptIdsConditionOccurrencePrimaryInpatientAnyTimePrior = c(),
conceptIdsConditionOccurrencePrimaryInpatientLongTerm = c(),
conceptIdsConditionOccurrencePrimaryInpatientMediumTerm = c(),
conceptIdsConditionOccurrencePrimaryInpatientShortTerm = c(),
conceptIdsConditionEraAnyTimePrior = c(),
conceptIdsConditionEraLongTerm = c(),
conceptIdsConditionEraMediumTerm = c(),
conceptIdsConditionEraShortTerm = c(),
conceptIdsConditionEraOverlapping = c(),
conceptIdsConditionEraStartLongTerm = c(),
conceptIdsConditionEraStartMediumTerm = c(),
conceptIdsConditionEraStartShortTerm = c(),
conceptIdsConditionGroupEraAnyTimePrior = c(),
conceptIdsConditionGroupEraLongTerm = c(),
conceptIdsConditionGroupEraMediumTerm = c(),
conceptIdsConditionGroupEraShortTerm = c(),
conceptIdsConditionGroupEraOverlapping = c(),
conceptIdsConditionGroupEraStartLongTerm = c(),
conceptIdsConditionGroupEraStartMediumTerm = c(),
conceptIdsConditionGroupEraStartShortTerm = c(),
conceptIdsDrugExposureAnyTimePrior = c(),
conceptIdsDrugExposureLongTerm = c(),
conceptIdsDrugExposureMediumTerm = c(),
conceptIdsDrugExposureShortTerm = c(),
conceptIdsDrugEraAnyTimePrior = c(),
conceptIdsDrugEraLongTerm = c(),
conceptIdsDrugEraMediumTerm = c(),
conceptIdsDrugEraShortTerm = c(),
conceptIdsDrugEraOverlapping = c(),
conceptIdsDrugEraStartLongTerm = c(),
conceptIdsDrugEraStartMediumTerm = c(),
conceptIdsDrugEraStartShortTerm = c(),
conceptIdsDrugGroupEraAnyTimePrior = c(),
conceptIdsDrugGroupEraLongTerm = c(),
conceptIdsDrugGroupEraMediumTerm = c(),
conceptIdsDrugGroupEraShortTerm = c(),
conceptIdsDrugGroupEraOverlapping = c(),
conceptIdsDrugGroupEraStartLongTerm = c(),
conceptIdsDrugGroupEraStartMediumTerm = c(),
conceptIdsDrugGroupEraStartShortTerm = c(),
conceptIdsProcedureOccurrenceAnyTimePrior = c(),
conceptIdsProcedureOccurrenceLongTerm = c(),
conceptIdsProcedureOccurrenceMediumTerm = c(),
conceptIdsProcedureOccurrenceShortTerm = c(),
conceptIdsDeviceExposureAnyTimePrior = c(),
conceptIdsDeviceExposureLongTerm = c(),
conceptIdsDeviceExposureMediumTerm = c(),
conceptIdsDeviceExposureShortTerm = c(),
conceptIdsMeasurementAnyTimePrior = c(),
conceptIdsMeasurementLongTerm = c(),
conceptIdsMeasurementMediumTerm = c(),
conceptIdsMeasurementShortTerm = c(),
conceptIdsMeasurementValueAnyTimePrior = c(),
conceptIdsMeasurementValueLongTerm = c(),
conceptIdsMeasurementValueMediumTerm = c(),
conceptIdsMeasurementValueShortTerm = c(),
conceptIdsMeasurementRangeGroupAnyTimePrior = c(),
conceptIdsMeasurementRangeGroupLongTerm = c(),
conceptIdsMeasurementRangeGroupMediumTerm = c(),
conceptIdsMeasurementRangeGroupShortTerm = c(),
conceptIdsObservationAnyTimePrior = c(),
conceptIdsObservationLongTerm = c(),
conceptIdsObservationMediumTerm = c(),
conceptIdsObservationShortTerm = c(),
useCharlsonIndex = FALSE,
useDcsi = FALSE,
useChads2 = FALSE,
useChads2Vasc = FALSE,
useHfrs = FALSE,
useDistinctConditionCountLongTerm = FALSE,
useDistinctConditionCountMediumTerm = FALSE,
useDistinctConditionCountShortTerm = FALSE,
useDistinctIngredientCountLongTerm = FALSE,
useDistinctIngredientCountMediumTerm = FALSE,
useDistinctIngredientCountShortTerm = FALSE,
useDistinctProcedureCountLongTerm = FALSE,
useDistinctProcedureCountMediumTerm = FALSE,
useDistinctProcedureCountShortTerm = FALSE,
useDistinctMeasurementCountLongTerm = FALSE,
useDistinctMeasurementCountMediumTerm = FALSE,
useDistinctMeasurementCountShortTerm = FALSE,
useDistinctObservationCountLongTerm = FALSE,
useDistinctObservationCountMediumTerm = FALSE,
useDistinctObservationCountShortTerm = FALSE,
useVisitCountLongTerm = FALSE,
useVisitCountMediumTerm = FALSE,
useVisitCountShortTerm = FALSE,
useVisitConceptCountLongTerm = FALSE,
useVisitConceptCountMediumTerm = FALSE,
useVisitConceptCountShortTerm = FALSE,
longTermStartDays = -365,
mediumTermStartDays = -180,
shortTermStartDays = -30,
endDays = 0){
covariateSetting <- FeatureExtraction::createCovariateSettings(useDemographicsGender = useDemographicsGender,
useDemographicsAge = useDemographicsAge,
useDemographicsAgeGroup = useDemographicsAgeGroup,
useDemographicsRace = useDemographicsRace,
useDemographicsEthnicity = useDemographicsEthnicity,
useDemographicsIndexYear = useDemographicsIndexYear,
useDemographicsIndexMonth = useDemographicsIndexMonth,
useDemographicsPriorObservationTime = useDemographicsPriorObservationTime,
useDemographicsPostObservationTime = useDemographicsPostObservationTime,
useDemographicsTimeInCohort = useDemographicsTimeInCohort,
useDemographicsIndexYearMonth = useDemographicsIndexYearMonth,
useConditionOccurrenceAnyTimePrior = as.logical(length(conceptIdsConditionOccurrenceAnyTimePrior)),
useConditionOccurrenceLongTerm = as.logical(length(conceptIdsConditionOccurrenceLongTerm)),
useConditionOccurrenceMediumTerm = as.logical(length(conceptIdsConditionOccurrenceMediumTerm)),
useConditionOccurrenceShortTerm = as.logical(length(conceptIdsConditionOccurrenceShortTerm)),
useConditionOccurrencePrimaryInpatientAnyTimePrior = as.logical(length(conceptIdsConditionOccurrencePrimaryInpatientAnyTimePrior)),
useConditionOccurrencePrimaryInpatientLongTerm = as.logical(length(conceptIdsConditionOccurrencePrimaryInpatientLongTerm)),
useConditionOccurrencePrimaryInpatientMediumTerm = as.logical(length(conceptIdsConditionOccurrencePrimaryInpatientMediumTerm)),
useConditionOccurrencePrimaryInpatientShortTerm = as.logical(length(conceptIdsConditionOccurrencePrimaryInpatientShortTerm)),
useConditionEraAnyTimePrior = as.logical(length(conceptIdsConditionEraAnyTimePrior)),
useConditionEraLongTerm = as.logical(length(conceptIdsConditionEraLongTerm)),
useConditionEraMediumTerm = as.logical(length(conceptIdsConditionEraMediumTerm)),
useConditionEraShortTerm = as.logical(length(conceptIdsConditionEraShortTerm)),
useConditionEraOverlapping = as.logical(length(conceptIdsConditionEraOverlapping)),
useConditionEraStartLongTerm = as.logical(length(conceptIdsConditionEraStartLongTerm)),
useConditionEraStartMediumTerm = as.logical(length(conceptIdsConditionEraStartMediumTerm)),
useConditionEraStartShortTerm = as.logical(length(conceptIdsConditionEraStartShortTerm)),
useConditionGroupEraAnyTimePrior = as.logical(length(conceptIdsConditionGroupEraAnyTimePrior)),
useConditionGroupEraLongTerm = as.logical(length(conceptIdsConditionGroupEraLongTerm)),
useConditionGroupEraMediumTerm = as.logical(length(conceptIdsConditionGroupEraMediumTerm)),
useConditionGroupEraShortTerm = as.logical(length(conceptIdsConditionGroupEraShortTerm)),
useConditionGroupEraOverlapping = as.logical(length(conceptIdsConditionGroupEraOverlapping)),
useConditionGroupEraStartLongTerm = as.logical(length(conceptIdsConditionGroupEraStartLongTerm)),
useConditionGroupEraStartMediumTerm = as.logical(length(conceptIdsConditionGroupEraStartMediumTerm)),
useConditionGroupEraStartShortTerm = as.logical(length(conceptIdsConditionGroupEraStartShortTerm)),
useDrugExposureAnyTimePrior = as.logical(length(conceptIdsDrugExposureAnyTimePrior)),
useDrugExposureLongTerm = as.logical(length(conceptIdsDrugExposureLongTerm)),
useDrugExposureMediumTerm = as.logical(length(conceptIdsDrugExposureMediumTerm)),
useDrugExposureShortTerm = as.logical(length(conceptIdsDrugExposureShortTerm)),
useDrugEraAnyTimePrior = as.logical(length(conceptIdsDrugEraAnyTimePrior)),
useDrugEraLongTerm = as.logical(length(conceptIdsDrugEraLongTerm)),
useDrugEraMediumTerm = as.logical(length(conceptIdsDrugEraMediumTerm)),
useDrugEraShortTerm = as.logical(length(conceptIdsDrugEraShortTerm)),
useDrugEraOverlapping = as.logical(length(conceptIdsDrugEraOverlapping)),
useDrugEraStartLongTerm = as.logical(length(conceptIdsDrugEraStartLongTerm)),
useDrugEraStartMediumTerm = as.logical(length(conceptIdsDrugEraStartMediumTerm)),
useDrugEraStartShortTerm = as.logical(length(conceptIdsDrugEraStartShortTerm)),
useDrugGroupEraAnyTimePrior = as.logical(length(conceptIdsDrugGroupEraAnyTimePrior)),
useDrugGroupEraLongTerm = as.logical(length(conceptIdsDrugGroupEraLongTerm)),
useDrugGroupEraMediumTerm = as.logical(length(conceptIdsDrugGroupEraMediumTerm)),
useDrugGroupEraShortTerm = as.logical(length(conceptIdsDrugGroupEraShortTerm)),
useDrugGroupEraOverlapping = as.logical(length(conceptIdsDrugGroupEraOverlapping)),
useDrugGroupEraStartLongTerm = as.logical(length(conceptIdsDrugGroupEraStartLongTerm)),
useDrugGroupEraStartMediumTerm = as.logical(length(conceptIdsDrugGroupEraStartMediumTerm)),
useDrugGroupEraStartShortTerm = as.logical(length(conceptIdsDrugGroupEraStartShortTerm)),
useProcedureOccurrenceAnyTimePrior = as.logical(length(conceptIdsProcedureOccurrenceAnyTimePrior)),
useProcedureOccurrenceLongTerm = as.logical(length(conceptIdsProcedureOccurrenceLongTerm)),
useProcedureOccurrenceMediumTerm = as.logical(length(conceptIdsProcedureOccurrenceMediumTerm)),
useProcedureOccurrenceShortTerm = as.logical(length(conceptIdsProcedureOccurrenceShortTerm)),
useDeviceExposureAnyTimePrior = as.logical(length(conceptIdsDeviceExposureAnyTimePrior)),
useDeviceExposureLongTerm = as.logical(length(conceptIdsDeviceExposureLongTerm)),
useDeviceExposureMediumTerm = as.logical(length(conceptIdsDeviceExposureMediumTerm)),
useDeviceExposureShortTerm = as.logical(length(conceptIdsDeviceExposureShortTerm)),
useMeasurementAnyTimePrior = as.logical(length(conceptIdsMeasurementAnyTimePrior)),
useMeasurementLongTerm = as.logical(length(conceptIdsMeasurementLongTerm)),
useMeasurementMediumTerm = as.logical(length(conceptIdsMeasurementMediumTerm)),
useMeasurementShortTerm = as.logical(length(conceptIdsMeasurementShortTerm)),
useMeasurementValueAnyTimePrior = as.logical(length(conceptIdsMeasurementValueAnyTimePrior)),
useMeasurementValueLongTerm = as.logical(length(conceptIdsMeasurementValueLongTerm)),
useMeasurementValueMediumTerm = as.logical(length(conceptIdsMeasurementValueMediumTerm)),
useMeasurementValueShortTerm = as.logical(length(conceptIdsMeasurementValueShortTerm)),
useMeasurementRangeGroupAnyTimePrior = as.logical(length(conceptIdsMeasurementRangeGroupAnyTimePrior)),
useMeasurementRangeGroupLongTerm = as.logical(length(conceptIdsMeasurementRangeGroupLongTerm)),
useMeasurementRangeGroupMediumTerm = as.logical(length(conceptIdsMeasurementRangeGroupMediumTerm)),
useMeasurementRangeGroupShortTerm = as.logical(length(conceptIdsMeasurementRangeGroupShortTerm)),
useObservationAnyTimePrior = as.logical(length(conceptIdsObservationAnyTimePrior)),
useObservationLongTerm = as.logical(length(conceptIdsObservationLongTerm)),
useObservationMediumTerm = as.logical(length(conceptIdsObservationMediumTerm)),
useObservationShortTerm = as.logical(length(conceptIdsObservationShortTerm)),
useCharlsonIndex = useCharlsonIndex,
useDcsi = useDcsi,
useChads2 = useChads2,
useChads2Vasc = useChads2Vasc,
useHfrs = useHfrs,
useDistinctConditionCountLongTerm = useDistinctConditionCountLongTerm,
useDistinctConditionCountMediumTerm = useDistinctConditionCountMediumTerm,
useDistinctConditionCountShortTerm = useDistinctConditionCountShortTerm,
useDistinctIngredientCountLongTerm = useDistinctIngredientCountLongTerm,
useDistinctIngredientCountMediumTerm = useDistinctIngredientCountMediumTerm,
useDistinctIngredientCountShortTerm = useDistinctIngredientCountShortTerm,
useDistinctProcedureCountLongTerm = useDistinctProcedureCountLongTerm,
useDistinctProcedureCountMediumTerm = useDistinctProcedureCountMediumTerm,
useDistinctProcedureCountShortTerm = useDistinctProcedureCountShortTerm,
useDistinctMeasurementCountLongTerm = useDistinctMeasurementCountLongTerm,
useDistinctMeasurementCountMediumTerm = useDistinctMeasurementCountMediumTerm,
useDistinctMeasurementCountShortTerm = useDistinctMeasurementCountShortTerm,
useDistinctObservationCountLongTerm = useDistinctObservationCountLongTerm,
useDistinctObservationCountMediumTerm = useDistinctObservationCountMediumTerm,
useDistinctObservationCountShortTerm = useDistinctObservationCountShortTerm,
useVisitCountLongTerm = useVisitCountLongTerm,
useVisitCountMediumTerm = useVisitCountMediumTerm,
useVisitCountShortTerm = useVisitCountShortTerm,
useVisitConceptCountLongTerm = useVisitConceptCountLongTerm,
useVisitConceptCountMediumTerm = useVisitConceptCountMediumTerm,
useVisitConceptCountShortTerm = useVisitConceptCountShortTerm,
longTermStartDays = longTermStartDays,
mediumTermStartDays = mediumTermStartDays,
shortTermStartDays = shortTermStartDays,
endDays = endDays)
label <- c()
analysisId <- c()
covariateIds <- c()
if(useDemographicsGender){
label <- c(label, "Gender")
analysisId <- c(analysisId, 1)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",8532,1),collapse=","))
}
if(useDemographicsAge){
label <- c(label, "Age")
analysisId <- c(analysisId, 2)
covariateIds <- c(covariateIds, "")
}
if(useDemographicsAgeGroup){
label <- c(label, "Age Group")
analysisId <- c(analysisId, 3)
covariateIds <- c(covariateIds, "")
}
if(useDemographicsRace){
label <- c(label, "Race")
analysisId <- c(analysisId, 4)
covariateIds <- c(covariateIds, "")
}
if(useDemographicsEthnicity){
label <- c(label, "Ethnicity")
analysisId <- c(analysisId, 5)
covariateIds <- c(covariateIds, "")
}
if(useDemographicsIndexYear){
label <- c(label, "Index year")
analysisId <- c(analysisId, 6)
covariateIds <- c(covariateIds, "")
}
if(useDemographicsIndexMonth){
label <- c(label, "Index month")
analysisId <- c(analysisId, 7)
covariateIds <- c(covariateIds, "")
}
if(useDemographicsPriorObservationTime){
label <- c(label, "Prior obesrvation time")
analysisId <- c(analysisId, 8)
covariateIds <- c(covariateIds, "")
}
if(useDemographicsPostObservationTime){
label <- c(label, "Post observation time")
analysisId <- c(analysisId, 9)
covariateIds <- c(covariateIds, "")
}
if(useDemographicsTimeInCohort){
label <- c(label, "Time in cohort")
analysisId <- c(analysisId, 10)
covariateIds <- c(covariateIds, "")
}
if(useDemographicsIndexYearMonth){
label <- c(label, "Index year month")
analysisId <- c(analysisId, 11)
covariateIds <- c(covariateIds, "")
}
if(length(conceptIdsConditionOccurrenceAnyTimePrior)){
label <- c(label, "ConditionOccurrenceAnyTimePrior")
analysisId <- c(analysisId, 101)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionOccurrenceAnyTimePrior,101),collapse=","))
}
if(length(conceptIdsConditionOccurrenceLongTerm)){
label <- c(label, "ConditionOccurrenceLongTerm")
analysisId <- c(analysisId, 102)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionOccurrenceLongTerm,102),collapse=","))
}
if(length(conceptIdsConditionOccurrenceMediumTerm)){
label <- c(label, "ConditionOccurrenceMediumTerm")
analysisId <- c(analysisId, 103)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionOccurrenceMediumTerm,103),collapse=","))
}
if(length(conceptIdsConditionOccurrenceShortTerm)){
label <- c(label, "ConditionOccurrenceShortTerm")
analysisId <- c(analysisId, 104)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionOccurrenceShortTerm,104),collapse=","))
}
if(length(conceptIdsConditionOccurrencePrimaryInpatientAnyTimePrior)){
label <- c(label, "ConditionOccurrencePrimaryInpatientAnyTimePrior")
analysisId <- c(analysisId, 105)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionOccurrencePrimaryInpatientAnyTimePrior,105),collapse=","))
}
if(length(conceptIdsConditionOccurrencePrimaryInpatientLongTerm)){
label <- c(label, "ConditionOccurrencePrimaryInpatientLongTerm")
analysisId <- c(analysisId, 106)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionOccurrencePrimaryInpatientLongTerm,106),collapse=","))
}
if(length(conceptIdsConditionOccurrencePrimaryInpatientMediumTerm)){
label <- c(label, "ConditionOccurrencePrimaryInpatientMediumTerm")
analysisId <- c(analysisId, 107)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionOccurrencePrimaryInpatientMediumTerm,107),collapse=","))
}
if(length(conceptIdsConditionOccurrencePrimaryInpatientShortTerm)){
label <- c(label, "ConditionOccurrencePrimaryInpatientShortTerm")
analysisId <- c(analysisId, 108)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionOccurrencePrimaryInpatientShortTerm,108),collapse=","))
}
if(length(conceptIdsConditionEraAnyTimePrior)){
label <- c(label, "ConditionEraAnyTimePrior")
analysisId <- c(analysisId, 201)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionEraAnyTimePrior,201),collapse=","))
}
if(length(conceptIdsConditionEraLongTerm)){
label <- c(label, "ConditionEraLongTerm")
analysisId <- c(analysisId, 202)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionEraLongTerm,202),collapse=","))
}
if(length(conceptIdsConditionEraMediumTerm)){
label <- c(label, "ConditionEraMediumTerm")
analysisId <- c(analysisId, 203)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionEraMediumTerm,203),collapse=","))
}
if(length(conceptIdsConditionEraShortTerm)){
label <- c(label, "ConditionEraShortTerm")
analysisId <- c(analysisId, 204)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionEraShortTerm,204),collapse=","))
}
if(length(conceptIdsConditionEraOverlapping)){
label <- c(label, "ConditionEraOverlapping")
analysisId <- c(analysisId, 205)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionEraOverlapping,205),collapse=","))
}
if(length(conceptIdsConditionEraStartLongTerm)){
label <- c(label, "ConditionEraStartLongTerm")
analysisId <- c(analysisId, 206)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionEraStartLongTerm,206),collapse=","))
}
if(length(conceptIdsConditionEraStartMediumTerm)){
label <- c(label, "ConditionEraStartMediumTerm")
analysisId <- c(analysisId, 207)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionEraStartMediumTerm,207),collapse=","))
}
if(length(conceptIdsConditionEraStartShortTerm)){
label <- c(label, "ConditionEraStartShortTerm")
analysisId <- c(analysisId, 208)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionEraStartShortTerm,208),collapse=","))
}
if(length(conceptIdsConditionGroupEraAnyTimePrior)){
label <- c(label, "ConditionGroupEraAnyTimePrior")
analysisId <- c(analysisId, 209)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionGroupEraAnyTimePrior,209),collapse=","))
}
if(length(conceptIdsConditionGroupEraLongTerm)){
label <- c(label, "ConditionGroupEraLongTerm")
analysisId <- c(analysisId, 210)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionGroupEraLongTerm,210),collapse=","))
}
if(length(conceptIdsConditionGroupEraMediumTerm)){
label <- c(label, "ConditionGroupEraMediumTerm")
analysisId <- c(analysisId, 211)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionGroupEraMediumTerm,211),collapse=","))
}
if(length(conceptIdsConditionGroupEraShortTerm)){
label <- c(label, "ConditionGroupEraShortTerm")
analysisId <- c(analysisId, 212)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionGroupEraShortTerm,212),collapse=","))
}
if(length(conceptIdsConditionGroupEraOverlapping)){
label <- c(label, "ConditionGroupEraOverlapping")
analysisId <- c(analysisId, 213)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionGroupEraOverlapping,213),collapse=","))
}
if(length(conceptIdsConditionGroupEraStartLongTerm)){
label <- c(label, "ConditionGroupEraStartLongTerm")
analysisId <- c(analysisId, 214)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionGroupEraStartLongTerm,214),collapse=","))
}
if(length(conceptIdsConditionGroupEraStartMediumTerm)){
label <- c(label, "ConditionGroupEraStartMediumTerm")
analysisId <- c(analysisId, 215)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionGroupEraStartMediumTerm,215),collapse=","))
}
if(length(conceptIdsConditionGroupEraStartShortTerm)){
label <- c(label, "ConditionGroupEraStartShortTerm")
analysisId <- c(analysisId, 216)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsConditionGroupEraStartShortTerm,216),collapse=","))
}
if(length(conceptIdsDrugExposureAnyTimePrior)){
label <- c(label, "DrugExposureAnyTimePrior")
analysisId <- c(analysisId, 301)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugExposureAnyTimePrior,301),collapse=","))
}
if(length(conceptIdsDrugExposureLongTerm)){
label <- c(label, "DrugExposureLongTerm")
analysisId <- c(analysisId, 302)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugExposureLongTerm,302),collapse=","))
}
if(length(conceptIdsDrugExposureMediumTerm)){
label <- c(label, "DrugExposureMediumTerm")
analysisId <- c(analysisId, 303)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugExposureMediumTerm,303),collapse=","))
}
if(length(conceptIdsDrugExposureShortTerm)){
label <- c(label, "DrugExposureShortTerm")
analysisId <- c(analysisId, 304)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugExposureShortTerm,304),collapse=","))
}
if(length(conceptIdsDrugEraAnyTimePrior)){
label <- c(label, "DrugEraAnyTimePrior")
analysisId <- c(analysisId, 401)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugEraAnyTimePrior,401),collapse=","))
}
if(length(conceptIdsDrugEraLongTerm)){
label <- c(label, "DrugEraLongTerm")
analysisId <- c(analysisId, 402)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugEraLongTerm,402),collapse=","))
}
if(length(conceptIdsDrugEraMediumTerm)){
label <- c(label, "DrugEraMediumTerm")
analysisId <- c(analysisId, 403)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugEraMediumTerm,403),collapse=","))
}
if(length(conceptIdsDrugEraShortTerm)){
label <- c(label, "DrugEraShortTerm")
analysisId <- c(analysisId, 404)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugEraShortTerm,404),collapse=","))
}
if(length(conceptIdsDrugEraOverlapping)){
label <- c(label, "DrugEraOverlapping")
analysisId <- c(analysisId, 405)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugEraOverlapping,405),collapse=","))
}
if(length(conceptIdsDrugEraStartLongTerm)){
label <- c(label, "DrugEraStartLongTerm")
analysisId <- c(analysisId, 406)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugEraStartLongTerm,406),collapse=","))
}
if(length(conceptIdsDrugEraStartMediumTerm)){
label <- c(label, "DrugEraStartMediumTerm")
analysisId <- c(analysisId, 407)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugEraStartMediumTerm,407),collapse=","))
}
if(length(conceptIdsDrugEraStartShortTerm)){
label <- c(label, "DrugEraStartShortTerm")
analysisId <- c(analysisId, 408)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugEraStartShortTerm,408),collapse=","))
}
if(length(conceptIdsDrugGroupEraAnyTimePrior)){
label <- c(label, "DrugGroupEraAnyTimePrior")
analysisId <- c(analysisId, 409)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugGroupEraAnyTimePrior,409),collapse=","))
}
if(length(conceptIdsDrugGroupEraLongTerm)){
label <- c(label, "DrugGroupEraLongTerm")
analysisId <- c(analysisId, 410)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugGroupEraLongTerm,410),collapse=","))
}
if(length(conceptIdsDrugGroupEraMediumTerm)){
label <- c(label, "DrugGroupEraMediumTerm")
analysisId <- c(analysisId, 411)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugGroupEraMediumTerm,411),collapse=","))
}
if(length(conceptIdsDrugGroupEraShortTerm)){
label <- c(label, "DrugGroupEraShortTerm")
analysisId <- c(analysisId, 412)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugGroupEraShortTerm,412),collapse=","))
}
if(length(conceptIdsDrugGroupEraOverlapping)){
label <- c(label, "DrugGroupEraOverlapping")
analysisId <- c(analysisId, 413)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugGroupEraOverlapping,413),collapse=","))
}
if(length(conceptIdsDrugGroupEraStartLongTerm)){
label <- c(label, "DrugGroupEraStartLongTerm")
analysisId <- c(analysisId, 414)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugGroupEraStartLongTerm,414),collapse=","))
}
if(length(conceptIdsDrugGroupEraStartMediumTerm)){
label <- c(label, "DrugGroupEraStartMediumTerm")
analysisId <- c(analysisId, 415)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugGroupEraStartMediumTerm,415),collapse=","))
}
if(length(conceptIdsDrugGroupEraStartShortTerm)){
label <- c(label, "DrugGroupEraStartShortTerm")
analysisId <- c(analysisId, 416)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDrugGroupEraStartShortTerm,416),collapse=","))
}
if(length(conceptIdsProcedureOccurrenceAnyTimePrior)){
label <- c(label, "ProcedureOccurrenceAnyTimePrior")
analysisId <- c(analysisId, 501)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsProcedureOccurrenceAnyTimePrior,501),collapse=","))
}
if(length(conceptIdsProcedureOccurrenceLongTerm)){
label <- c(label, "ProcedureOccurrenceLongTerm")
analysisId <- c(analysisId, 502)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsProcedureOccurrenceLongTerm,502),collapse=","))
}
if(length(conceptIdsProcedureOccurrenceMediumTerm)){
label <- c(label, "ProcedureOccurrenceMediumTerm")
analysisId <- c(analysisId, 503)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsProcedureOccurrenceMediumTerm,503),collapse=","))
}
if(length(conceptIdsProcedureOccurrenceShortTerm)){
label <- c(label, "ProcedureOccurrenceShortTerm")
analysisId <- c(analysisId, 504)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsProcedureOccurrenceShortTerm,504),collapse=","))
}
if(length(conceptIdsDeviceExposureAnyTimePrior)){
label <- c(label, "DeviceExposureAnyTimePrior")
analysisId <- c(analysisId, 601)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDeviceExposureAnyTimePrior,601),collapse=","))
}
if(length(conceptIdsDeviceExposureLongTerm)){
label <- c(label, "DeviceExposureLongTerm")
analysisId <- c(analysisId, 602)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDeviceExposureLongTerm,602),collapse=","))
}
if(length(conceptIdsDeviceExposureMediumTerm)){
label <- c(label, "DeviceExposureMediumTerm")
analysisId <- c(analysisId, 603)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDeviceExposureMediumTerm,603),collapse=","))
}
if(length(conceptIdsDeviceExposureShortTerm)){
label <- c(label, "DeviceExposureShortTerm")
analysisId <- c(analysisId, 604)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsDeviceExposureShortTerm,604),collapse=","))
}
if(length(conceptIdsMeasurementAnyTimePrior)){
label <- c(label, "MeasurementAnyTimePrior")
analysisId <- c(analysisId, 701)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsMeasurementAnyTimePrior,701),collapse=","))
}
if(length(conceptIdsMeasurementLongTerm)){
label <- c(label, "MeasurementLongTerm")
analysisId <- c(analysisId, 702)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsMeasurementLongTerm,702),collapse=","))
}
if(length(conceptIdsMeasurementMediumTerm)){
label <- c(label, "MeasurementMediumTerm")
analysisId <- c(analysisId, 703)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsMeasurementMediumTerm,703),collapse=","))
}
if(length(conceptIdsMeasurementShortTerm)){
label <- c(label, "MeasurementShortTerm")
analysisId <- c(analysisId, 704)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsMeasurementShortTerm,704),collapse=","))
}
if(length(conceptIdsMeasurementValueAnyTimePrior)){
label <- c(label, "MeasurementValueAnyTimePrior")
analysisId <- c(analysisId, 705)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsMeasurementValueAnyTimePrior,705),collapse=","))
}
if(length(conceptIdsMeasurementValueLongTerm)){
label <- c(label, "MeasurementValueLongTerm")
analysisId <- c(analysisId, 706)
covariateIds <- c(covariateIds, paste0(sprintf("%s%03d",conceptIdsMeasurementValueLongTerm,706),collapse=","))
}
if(length(conceptIdsMeasurementValueMediumTerm)){
label <- c(label, "MeasurementValueMediumTerm")
analysisId <- c(analysisId, 707)
covariateIds <- c(covariateIds, paste0(sprintf("%s%03d",conceptIdsMeasurementValueMediumTerm,707),collapse=","))
}
if(length(conceptIdsMeasurementValueShortTerm)){
label <- c(label, "MeasurementValueShortTerm")
analysisId <- c(analysisId, 708)
covariateIds <- c(covariateIds, paste0(sprintf("%s%03d",conceptIdsMeasurementValueShortTerm,708),collapse=","))
}
if(length(conceptIdsMeasurementRangeGroupAnyTimePrior)){
label <- c(label, "MeasurementRangeGroupAnyTimePrior")
analysisId <- c(analysisId, 709)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsMeasurementRangeGroupAnyTimePrior,709),collapse=","))
}
if(length(conceptIdsMeasurementRangeGroupLongTerm)){
label <- c(label, "MeasurementRangeGroupLongTerm")
analysisId <- c(analysisId, 710)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsMeasurementRangeGroupLongTerm,710),collapse=","))
}
if(length(conceptIdsMeasurementRangeGroupMediumTerm)){
label <- c(label, "MeasurementRangeGroupMediumTerm")
analysisId <- c(analysisId, 711)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsMeasurementRangeGroupMediumTerm,711),collapse=","))
}
if(length(conceptIdsMeasurementRangeGroupShortTerm)){
label <- c(label, "MeasurementRangeGroupShortTerm")
analysisId <- c(analysisId, 712)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsMeasurementRangeGroupShortTerm,712),collapse=","))
}
if(length(conceptIdsObservationAnyTimePrior)){
label <- c(label, "ObservationAnyTimePrior")
analysisId <- c(analysisId, 801)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsObservationAnyTimePrior,801),collapse=","))
}
if(length(conceptIdsObservationLongTerm)){
label <- c(label, "ObservationLongTerm")
analysisId <- c(analysisId, 802)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsObservationLongTerm,802),collapse=","))
}
if(length(conceptIdsObservationMediumTerm)){
label <- c(label, "ObservationMediumTerm")
analysisId <- c(analysisId, 803)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsObservationMediumTerm,803),collapse=","))
}
if(length(conceptIdsObservationShortTerm)){
label <- c(label, "ObservationShortTerm")
analysisId <- c(analysisId, 804)
covariateIds <- c(covariateIds, paste0(sprintf("%d%03d",conceptIdsObservationShortTerm,804),collapse=","))
}
if(useCharlsonIndex){
label <- c(label, "CharlsonIndex")
analysisId <- c(analysisId, 901)
covariateIds <- c(covariateIds, "")
}
if(useDcsi){
label <- c(label, "Dcsi")
analysisId <- c(analysisId, 902)
covariateIds <- c(covariateIds, "")
}
if(useChads2){
label <- c(label, "Chads2")
analysisId <- c(analysisId, 903)
covariateIds <- c(covariateIds, "")
}
if(useChads2Vasc){
label <- c(label, "Chads2Vasc")
analysisId <- c(analysisId, 904)
covariateIds <- c(covariateIds, "")
}
if(useHfrs){
label <- c(label, "Hfrs")
analysisId <- c(analysisId, 926)
covariateIds <- c(covariateIds, "")
}
if(useDistinctConditionCountLongTerm){
label <- c(label, "DistinctConditionCountLongTerm")
analysisId <- c(analysisId, 905)
covariateIds <- c(covariateIds, "")
}
if(useDistinctConditionCountMediumTerm){
label <- c(label, "DistinctConditionCountMediumTerm")
analysisId <- c(analysisId, 906)
covariateIds <- c(covariateIds, "")
}
if(useDistinctConditionCountShortTerm){
label <- c(label, "DistinctConditionCountShortTerm")
analysisId <- c(analysisId, 907)
covariateIds <- c(covariateIds, "")
}
if(useDistinctIngredientCountLongTerm){
label <- c(label, "DistinctIngredientCountLongTerm")
analysisId <- c(analysisId, 908)
covariateIds <- c(covariateIds, "")
}
if(useDistinctIngredientCountMediumTerm){
label <- c(label, "DistinctIngredientCountMediumTerm")
analysisId <- c(analysisId, 909)
covariateIds <- c(covariateIds, "")
}
if(useDistinctIngredientCountShortTerm){
label <- c(label, "DistinctIngredientCountShortTerm")
analysisId <- c(analysisId, 910)
covariateIds <- c(covariateIds, "")
}
if(useDistinctProcedureCountLongTerm){
label <- c(label, "DistinctProcedureCountLongTerm")
analysisId <- c(analysisId, 911)
covariateIds <- c(covariateIds, "")
}
if(useDistinctProcedureCountMediumTerm){
label <- c(label, "DistinctProcedureCountMediumTerm")
analysisId <- c(analysisId, 912)
covariateIds <- c(covariateIds, "")
}
if(useDistinctProcedureCountShortTerm){
label <- c(label, "DistinctProcedureCountShortTerm")
analysisId <- c(analysisId, 913)
covariateIds <- c(covariateIds, "")
}
if(useDistinctMeasurementCountLongTerm){
label <- c(label, "DistinctMeasurementCountLongTerm")
analysisId <- c(analysisId, 914)
covariateIds <- c(covariateIds, "")
}
if(useDistinctMeasurementCountMediumTerm){
label <- c(label, "DistinctMeasurementCountMediumTerm")
analysisId <- c(analysisId, 915)
covariateIds <- c(covariateIds, "")
}
if(useDistinctMeasurementCountShortTerm){
label <- c(label, "DistinctMeasurementCountShortTerm")
analysisId <- c(analysisId, 916)
covariateIds <- c(covariateIds, "")
}
if(useDistinctObservationCountLongTerm){
label <- c(label, "DistinctObservationCountLongTerm")
analysisId <- c(analysisId, 917)
covariateIds <- c(covariateIds, "")
}
if(useDistinctObservationCountMediumTerm){
label <- c(label, "DistinctObservationCountMediumTerm")
analysisId <- c(analysisId, 918)
covariateIds <- c(covariateIds, "")
}
if(useDistinctObservationCountShortTerm){
label <- c(label, "DistinctObservationCountShortTerm")
analysisId <- c(analysisId, 919)
covariateIds <- c(covariateIds, "")
}
if(useVisitCountLongTerm){
label <- c(label, "VisitCountLongTerm")
analysisId <- c(analysisId, 920)
covariateIds <- c(covariateIds, "")
}
if(useVisitCountMediumTerm){
label <- c(label, "VisitCountMediumTerm")
analysisId <- c(analysisId, 921)
covariateIds <- c(covariateIds, "")
}
if(useVisitCountShortTerm){
label <- c(label, "VisitCountShortTerm")
analysisId <- c(analysisId, 922)
covariateIds <- c(covariateIds, "")
}
if(useVisitConceptCountLongTerm){
label <- c(label, "VisitConceptCountLongTerm")
analysisId <- c(analysisId, 923)
covariateIds <- c(covariateIds, "")
}
if(useVisitConceptCountMediumTerm){
label <- c(label, "VisitConceptCountMediumTerm")
analysisId <- c(analysisId, 924)
covariateIds <- c(covariateIds, "")
}
if(useVisitConceptCountShortTerm){
label <- c(label, "VisitConceptCountShortTerm")
analysisId <- c(analysisId, 925)
covariateIds <- c(covariateIds, "")
}
tableSpec <- data.frame(label = label,
analysisId = analysisId,
covariateIds = covariateIds,
stringsAsFactors = F)
result <- list(tableSpec = tableSpec, covariateSetting = covariateSetting)
class(result) <- "tableSpecification"
return(result)
}
#' Create a table 1
#'
#' @description
#' Creates a formatted table of cohort characteristics, to be included in publications or reports.
#' Allows for creating a table describing a single cohort, or a table comparing two cohorts.
#'
#' @param covariateData1 The covariate data of the cohort to be included in the table.
#' @param covariateData2 The covariate data of the cohort to also be included, when comparing two
#' cohorts.
#' @param specifications Specifications of which covariates to display, and how.
#' @param output The output format for the table. Options are \code{output = "two columns"},
#' \code{output = "one column"}, or \code{output = "list"}.
#' @param showCounts Show the number of cohort entries having the binary covariate?
#' @param showPercent Show the percentage of cohort entries having the binary covariate?
#' @param percentDigits Number of digits to be used for percentages.
#' @param stdDiffDigits Number of digits to be used for the standardized differences.
#' @param valueDigits Number of digits to be used for the values of continuous variables.
#'
#' @return
#' A data frame, or, when \code{output = "list"} a list of two data frames.
#'
createTable1 <- function(covariateData1,
covariateData2 = NULL,
specifications = getDefaultTable1Specifications(),
output = "two columns",
showCounts = FALSE,
showPercent = TRUE,
percentDigits = 1,
valueDigits = 1,
stdDiffDigits = 2) {
comparison <- !is.null(covariateData2)
if (!is(covariateData1, "covariateData")) {
stop("covariateData1 is not of type 'covariateData'")
}
if (comparison && !is(covariateData2, "covariateData")) {
stop("covariateData2 is not of type 'covariateData'")
}
if (is.null(covariateData1$covariatesContinuous) && is.null(covariateData1$covariates$averageValue)) {
stop("Covariate1 data is not aggregated")
}
if (comparison && is.null(covariateData2$covariatesContinuous) && is.null(covariateData2$covariates$averageValue)) {
stop("Covariate2 data is not aggregated")
}
if (!showCounts && !showPercent) {
stop("Must show counts or percent, or both")
}
fixCase <- function(label) {
idx <- (toupper(label) == label)
if (any(idx)) {
label[idx] <- paste0(substr(label[idx], 1, 1),
tolower(substr(label[idx], 2, nchar(label[idx]))))
}
return(label)
}
formatCount <- function(x) {
result <- format(round(x), justify = "right", big.mark = ",")
result <- gsub("NA", "", result)
result <- gsub(" ", " ", result)
return(result)
}
formatPercent <- function(x) {
result <- format(round(100*x, percentDigits), digits = percentDigits + 1, justify = "right")
result <- gsub("NA", "", result)
result <- gsub(" ", " ", result)
return(result)
}
formatStdDiff <- function(x) {
result <- format(round(x, stdDiffDigits), digits = stdDiffDigits + 1, justify = "right")
result <- gsub("NA", "", result)
result <- gsub(" ", " ", result)
return(result)
}
formatValue <- function(x) {
return(format(round(x, valueDigits), nsmall = valueDigits))
}
if (is.null(covariateData1$covariates)) {
covariates <- NULL
} else {
covariates <- as.data.frame(ff::as.ram(covariateData1$covariates[, c("covariateId", "sumValue", "averageValue")]))
colnames(covariates) <- c("covariateId", "count1", "percent1")
covariates$count1 <- formatCount(covariates$count1)
covariates$percent1 <- formatPercent(covariates$percent1)
}
if (is.null(covariateData1$covariatesContinuous)) {
covariatesContinuous <- NULL
} else {
covariatesContinuous <- as.data.frame(ff::as.ram(covariateData1$covariatesContinuous[, c("covariateId",
"averageValue",
"standardDeviation",
"minValue",
"p25Value",
"medianValue",
"p75Value",
"maxValue")]))
colnames(covariatesContinuous) <- c("covariateId",
"averageValue1",
"standardDeviation1",
"minValue1",
"p25Value1",
"medianValue1",
"p75Value1",
"maxValue1")
covariatesContinuous$averageValue1 <- formatValue(covariatesContinuous$averageValue1)
covariatesContinuous$standardDeviation1 <- formatValue(covariatesContinuous$standardDeviation1)
covariatesContinuous$minValue1 <- formatValue(covariatesContinuous$minValue1)
covariatesContinuous$p25Value1 <- formatValue(covariatesContinuous$p25Value1)
covariatesContinuous$medianValue1 <- formatValue(covariatesContinuous$medianValue1)
covariatesContinuous$p75Value1 <- formatValue(covariatesContinuous$p75Value1)
covariatesContinuous$maxValue1 <- formatValue(covariatesContinuous$maxValue1)
}
covariateRef <- ff::as.ram(covariateData1$covariateRef)
analysisRef <- ff::as.ram(covariateData1$analysisRef)
if (comparison) {
stdDiff <- FeatureExtraction::computeStandardizedDifference(covariateData1, covariateData2)
if (!is.null(covariateData1$covariates) && !is.null(covariateData2$covariates)) {
tempCovariates <- ff::as.ram(covariateData2$covariates[, c("covariateId", "sumValue", "averageValue")])
colnames(tempCovariates) <- c("covariateId", "count2", "percent2")
tempCovariates$count2 <- formatCount(tempCovariates$count2)
tempCovariates$percent2 <- formatPercent(tempCovariates$percent2)
covariates <- merge(covariates, tempCovariates, all = TRUE)
covariates$count1[is.na(covariates$count1)] <- " 0"
covariates$count2[is.na(covariates$count2)] <- " 0"
covariates$percent1[is.na(covariates$percent1)] <- " 0"
covariates$percent2[is.na(covariates$percent2)] <- " 0"
covariates <- merge(covariates, stdDiff[, c("covariateId", "stdDiff")])
covariates$stdDiff <- formatStdDiff(covariates$stdDiff)
}
if (!is.null(covariatesContinuous)) {
tempCovariates <- as.data.frame(ff::as.ram(covariateData2$covariatesContinuous[, c("covariateId",
"averageValue",
"standardDeviation",
"minValue",
"p25Value",
"medianValue",
"p75Value",
"maxValue")]))
colnames(tempCovariates) <- c("covariateId",
"averageValue2",
"standardDeviation2",
"minValue2",
"p25Value2",
"medianValue2",
"p75Value2",
"maxValue2")
tempCovariates$averageValue2 <- formatValue(tempCovariates$averageValue2)
tempCovariates$standardDeviation2 <- formatValue(tempCovariates$standardDeviation2)
tempCovariates$minValue2 <- formatValue(tempCovariates$minValue2)
tempCovariates$p25Value2 <- formatValue(tempCovariates$p25Value2)
tempCovariates$medianValue2 <- formatValue(tempCovariates$medianValue2)
tempCovariates$p75Value2 <- formatValue(tempCovariates$p75Value2)
tempCovariates$maxValue2 <- formatValue(tempCovariates$maxValue2)
covariatesContinuous <- merge(covariatesContinuous, tempCovariates, all = TRUE)
covariatesContinuous$averageValue1[is.na(covariatesContinuous$averageValue1)] <- " "
covariatesContinuous$standardDeviation1[is.na(covariatesContinuous$standardDeviation1)] <- " "
covariatesContinuous$minValue1[is.na(covariatesContinuous$minValue1)] <- " "
covariatesContinuous$p25Value1[is.na(covariatesContinuous$p25Value1)] <- " "
covariatesContinuous$medianValue1[is.na(covariatesContinuous$medianValue1)] <- " "
covariatesContinuous$p75Value1[is.na(covariatesContinuous$p75Value1)] <- " "
covariatesContinuous$maxValue1[is.na(covariatesContinuous$maxValue1)] <- " "
covariatesContinuous$averageValue2[is.na(covariatesContinuous$averageValue2)] <- " "
covariatesContinuous$standardDeviation2[is.na(covariatesContinuous$standardDeviation2)] <- " "
covariatesContinuous$minValue2[is.na(covariatesContinuous$minValue2)] <- " "
covariatesContinuous$p25Value2[is.na(covariatesContinuous$p25Value2)] <- " "
covariatesContinuous$medianValue2[is.na(covariatesContinuous$medianValue2)] <- " "
covariatesContinuous$p75Value2[is.na(covariatesContinuous$p75Value2)] <- " "
covariatesContinuous$maxValue2[is.na(covariatesContinuous$maxValue2)] <- " "
covariatesContinuous <- merge(covariatesContinuous, stdDiff[, c("covariateId", "stdDiff")])
covariatesContinuous$stdDiff <- formatStdDiff(covariatesContinuous$stdDiff)
}
idx <- !ffbase::`%in%`(covariateData2$covariateRef$covariateId,
covariateData1$covariateRef$covariateId)
if (ffbase::any.ff(idx)) {
covariateRef <- rbind(covariateRef, ff::as.ram(covariateData2$covariateRef[idx, ]))
}
} else {
covariates$count2 <- " 0"
covariates$percent2 <- " 0"
covariates$stdDiff <- " 0"
covariatesContinuous$averageValue2 <- " "
covariatesContinuous$standardDeviation2 <- " "
covariatesContinuous$minValue2 <- " "
covariatesContinuous$p25Value2 <- " "
covariatesContinuous$medianValue2 <- " "
covariatesContinuous$p75Value2 <- " "
covariatesContinuous$maxValue2 <- " "
covariatesContinuous$stdDiff <- " "
}
binaryTable <- data.frame()
continuousTable <- data.frame()
for (i in 1:nrow(specifications)) {
if (specifications$analysisId[i] == "") {
binaryTable <- rbind(binaryTable,
data.frame(Characteristic = specifications$label[i], value = ""))
} else {
idx <- analysisRef$analysisId == specifications$analysisId[i]
if (any(idx)) {
isBinary <- analysisRef$isBinary[idx]
covariateIds <- NULL
if (isBinary == "Y") {
# Binary
if (specifications$covariateIds[i] == "") {
idx <- covariateRef$analysisId == specifications$analysisId[i]
} else {
covariateIds <- as.numeric(strsplit(specifications$covariateIds[i], ",")[[1]])
idx <- covariateRef$covariateId %in% covariateIds
}
if (any(idx)) {
covariateRefSubset <- covariateRef[idx, ]
covariatesSubset <- merge(covariates, covariateRefSubset)
if (is.null(covariateIds)) {
covariatesSubset <- covariatesSubset[order(covariatesSubset$covariateId), ]
} else {
covariatesSubset <- merge(covariatesSubset, data.frame(covariateId = covariateIds,
rn = 1:length(covariateIds)))
covariatesSubset <- covariatesSubset[order(covariatesSubset$rn,
covariatesSubset$covariateId), ]
}
covariatesSubset$covariateName <- fixCase(gsub("^.*: ",
"",
covariatesSubset$covariateName))
if (specifications$covariateIds[i] == "" || length(covariateIds) > 1) {
binaryTable <- rbind(binaryTable, data.frame(Characteristic = specifications$label[i],
count1 = "",
percent1 = "",
count2 = "",
percent2 = "",
stdDiff = "",
stringsAsFactors = FALSE))
binaryTable <- rbind(binaryTable,
data.frame(Characteristic = paste0(" ", covariatesSubset$covariateName),
count1 = covariatesSubset$count1,
percent1 = covariatesSubset$percent1,
count2 = covariatesSubset$count2,
percent2 = covariatesSubset$percent2,
stdDiff = covariatesSubset$stdDiff,
stringsAsFactors = FALSE))
} else {
binaryTable <- rbind(binaryTable, data.frame(Characteristic = specifications$label[i],
count1 = covariatesSubset$count1,
percent1 = covariatesSubset$percent1,
count2 = covariatesSubset$count2,
percent2 = covariatesSubset$percent2,
stdDiff = covariatesSubset$stdDiff,
stringsAsFactors = FALSE))
}
}
} else {
# Not binary
if (specifications$covariateIds[i] == "") {
idx <- covariateRef$analysisId == specifications$analysisId[i]
} else {
covariateIds <- as.numeric(strsplit(specifications$covariateIds[i], ",")[[1]])
idx <- covariateRef$covariateId %in% covariateIds
}
if (any(idx)) {
covariateRefSubset <- covariateRef[idx, ]
covariatesSubset <- covariatesContinuous[covariatesContinuous$covariateId %in% covariateRefSubset$covariateId, ]
covariatesSubset <- merge(covariatesSubset, covariateRefSubset)
if (is.null(covariateIds)) {
covariatesSubset <- covariatesSubset[order(covariatesSubset$covariateId), ]
} else {
covariatesSubset <- merge(covariatesSubset, data.frame(covariateId = covariateIds,
rn = 1:length(covariateIds)))
covariatesSubset <- covariatesSubset[order(covariatesSubset$rn,
covariatesSubset$covariateId), ]
}
covariatesSubset$covariateName <- fixCase(gsub("^.*: ",
"",
covariatesSubset$covariateName))
if (specifications$covariateIds[i] == "" || length(covariateIds) > 1) {
continuousTable <- rbind(continuousTable,
data.frame(Characteristic = specifications$label[i],
value1 = "",
value2 = "",
stdDiff = "",
stringsAsFactors = FALSE))
for (j in 1:nrow(covariatesSubset)) {
continuousTable <- rbind(continuousTable,
data.frame(Characteristic = paste0(" ", covariatesSubset$covariateName[j]),
value1 = "",
value2 = "",
stdDiff = "",
stringsAsFactors = FALSE))
continuousTable <- rbind(continuousTable, data.frame(Characteristic = c(" Mean",
" Std. deviation",
" Minimum",
" 25th percentile",
" Median",
" 75th percentile",
" Maximum"),
value1 = c(covariatesSubset$averageValue1[j],
covariatesSubset$standardDeviation1[j],
covariatesSubset$minValue1[j],
covariatesSubset$p25Value1[j],
covariatesSubset$medianValue1[j],
covariatesSubset$p75Value1[j],
covariatesSubset$maxValue1[j]),
value2 = c(covariatesSubset$averageValue2[j],
covariatesSubset$standardDeviation2[j],
covariatesSubset$minValue2[j],
covariatesSubset$p25Value2[j],
covariatesSubset$medianValue2[j],
covariatesSubset$p75Value2[j],
covariatesSubset$maxValue2[j]),
stdDiff = c(covariatesSubset$stdDiff[j],
" ",
" ",
" ",
" ",
" ",
" "),
stringsAsFactors = FALSE))
}
} else {
continuousTable <- rbind(continuousTable,
data.frame(Characteristic = specifications$label[i],
value1 = "",
value2 = "",
stdDiff = "",
stringsAsFactors = FALSE))
continuousTable <- rbind(continuousTable, data.frame(Characteristic = c(" Mean",
" Std. deviation",
" Minimum",
" 25th percentile",
" Median",
" 75th percentile",
" Maximum"),
value1 = c(covariatesSubset$averageValue1,
covariatesSubset$standardDeviation1,
covariatesSubset$minValue1,
covariatesSubset$p25Value1,
covariatesSubset$medianValue1,
covariatesSubset$p75Value1,
covariatesSubset$maxValue1),
value2 = c(covariatesSubset$averageValue2,
covariatesSubset$standardDeviation2,
covariatesSubset$minValue2,
covariatesSubset$p25Value2,
covariatesSubset$medianValue2,
covariatesSubset$p75Value2,
covariatesSubset$maxValue2),
stdDiff = c(covariatesSubset$stdDiff,
" ",
" ",
" ",
" ",
" ",
" "),
stringsAsFactors = FALSE))
}
}
}
}
}
}
if (nrow(continuousTable) != 0) {
if (showCounts && showPercent) {
if (comparison) {
continuousTable$dummy1 <- ""
continuousTable$dummy2 <- ""
continuousTable <- continuousTable[, c(1, 5, 2, 6, 3, 4)]
colnames(continuousTable) <- c("Characteristic", "", "Value", "", "Value", "Std.Diff")
} else {
continuousTable$dummy <- ""
continuousTable <- continuousTable[, c(1,3,2)]
colnames(continuousTable) <- c("Characteristic", "", "Value")
}
} else {
if (comparison) {
colnames(continuousTable) <- c("Characteristic", "Value", "Value", "Std.Diff")
} else {
continuousTable$value2 <- NULL
continuousTable$stdDiff <- NULL
colnames(continuousTable) <- c("Characteristic", "Value")
}
}
}
if (nrow(binaryTable) != 0) {
if (comparison) {
colnames(binaryTable) <- c("Characteristic",
"Count",
paste0("% (n = ",
formatCount(covariateData1$metaData$populationSize),
")"),
"Count",
paste0("% (n = ",
formatCount(covariateData2$metaData$populationSize),
")"),
"Std.Diff")
if (!showCounts) {
binaryTable[, 4] <- NULL
binaryTable[, 2] <- NULL
}
if (!showPercent) {
binaryTable[, 5] <- NULL
binaryTable[, 3] <- NULL
}
} else {
binaryTable$count2 <- NULL
binaryTable$percent2 <- NULL
binaryTable$stdDiff <- NULL
colnames(binaryTable) <- c("Characteristic",
"Count",
paste0("% (n = ",
formatCount(covariateData1$metaData$populationSize),
")"))
if (!showCounts) {
binaryTable[, 2] <- NULL
}
if (!showPercent) {
binaryTable[, 3] <- NULL
}
}
}
if (output == "two columns") {
if (nrow(binaryTable) > nrow(continuousTable)) {
if (nrow(continuousTable) > 0) {
rowsPerColumn <- ceiling((nrow(binaryTable) + nrow(continuousTable) + 2)/2)
column1 <- binaryTable[1:rowsPerColumn, ]
ct <- continuousTable
colnames(ct) <- colnames(binaryTable)
column2 <- rbind(binaryTable[(rowsPerColumn + 1):nrow(binaryTable),
],
rep("", ncol(binaryTable)),
colnames(continuousTable),
ct)
} else {
rowsPerColumn <- ceiling((nrow(binaryTable) + nrow(continuousTable))/2)
column1 <- binaryTable[1:rowsPerColumn, ]
column2 <- binaryTable[(rowsPerColumn + 1):nrow(binaryTable), ]
}
if (nrow(column1) > nrow(column2)) {
column2 <- rbind(column2, rep("", ncol(binaryTable)))
}
result <- cbind(column1, column2)
} else {
stop("Don't know what to do when there are more rows in the table of continuous covariates than there are in the table of binary covariates.")
}
} else if (output == "one column") {
ct <- continuousTable
colnames(ct) <- colnames(binaryTable)
result <- rbind(binaryTable,
rep("", ncol(binaryTable)),
colnames(continuousTable),
ct)
} else {
result <- list(part1 = binaryTable, part2 = continuousTable)
}
return(result)
}
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