Package index • CohortMethod

Getting data and creating a study population

Functions for getting the necessary data from the database in Common Data Model, and creating a study population.

getDbCohortMethodData(): Get the cohort data from the server

show(<CohortMethodData>) summary(<CohortMethodData>): Cohort Method Data

isCohortMethodData(): Check whether an object is a CohortMethodData object

saveCohortMethodData(): Save the cohort method data to file

loadCohortMethodData(): Load the cohort method data from a file

createStudyPopulation(): Create a study population

Propensity scores

Functions for creating and using propensity scores.

createPs(): Create propensity scores

getPsModel(): Get the propensity model

matchOnPs(): Match persons by propensity score

matchOnPsAndCovariates(): Match by propensity score as well as other covariates

trimByPs(): Trim persons by propensity score

trimByPsToEquipoise(): Keep only persons in clinical equipoise

trimByIptw(): Remove subjects with a high IPTW

stratifyByPs(): Stratify persons by propensity score

stratifyByPsAndCovariates(): Stratify persons by propensity score and other covariates

truncateIptw(): Truncate IPTW values

Outcome models

Functions for creating and viewing outcome models.

fitOutcomeModel(): Create an outcome model, and compute the relative risk

getOutcomeModel(): Get the outcome model

adjustedKm(): Compute a weight-adjusted Kaplan-Meier curve

plotKaplanMeier(): Plot the Kaplan-Meier curve

Diagnostics

Functions for producing various study diagnostics.

computeMdrr(): Compute the minimum detectable relative risk

getAttritionTable(): Get the attrition table for a population

drawAttritionDiagram(): Draw the attrition diagram

plotFollowUpDistribution(): Plot the distribution of follow-up time

createCmTable1(): Create a table 1

getDefaultCmTable1Specifications(): Get the default table 1 specifications

getFollowUpDistribution(): Get the distribution of follow-up time

plotPs(): Plot the propensity score distribution

computeEquipoise(): Compute fraction in equipoise

computePsAuc(): Compute the area under the ROC curve

computeCovariateBalance(): Compute covariate balance before and after PS adjustment

plotCovariateBalanceOfTopVariables(): Plot variables with largest imbalance

plotCovariateBalanceScatterPlot(): Create a scatterplot of the covariate balance

plotCovariatePrevalence(): Plot covariate prevalence

plotTimeToEvent(): Plot time-to-event

getGeneralizabilityTable(): Get information on generalizability

Running multiple analyses

Functions for running multiple analyses in an efficient way.

createComputeCovariateBalanceArgs(): Create a parameter object for the function computeCovariateBalance

createCreatePsArgs(): Create a parameter object for the function createPs

createCreateStudyPopulationArgs(): Create a parameter object for the function createStudyPopulation

createFitOutcomeModelArgs(): Create a parameter object for the function fitOutcomeModel

createGetDbCohortMethodDataArgs(): Create a parameter object for the function getDbCohortMethodData

createMatchOnPsAndCovariatesArgs(): Create a parameter object for the function matchOnPsAndCovariates

createMatchOnPsArgs(): Create a parameter object for the function matchOnPs

createStratifyByPsAndCovariatesArgs(): Create a parameter object for the function stratifyByPsAndCovariates

createStratifyByPsArgs(): Create a parameter object for the function stratifyByPs

createTrimByIptwArgs(): Create a parameter object for the function trimByIptw

createTrimByPsArgs(): Create a parameter object for the function trimByPs

createTrimByPsToEquipoiseArgs(): Create a parameter object for the function trimByPsToEquipoise

createTruncateIptwArgs(): Create a parameter object for the function truncateIptw

createCmAnalysis(): Create a CohortMethod analysis specification

saveCmAnalysisList(): Save a list of cmAnalysis to file

loadCmAnalysisList(): Load a list of cmAnalysis from file

createOutcome(): Create outcome definition

createTargetComparatorOutcomes(): Create target-comparator-outcomes combinations.

saveTargetComparatorOutcomesList(): Save a list of targetComparatorOutcomes to file

loadTargetComparatorOutcomesList(): Load a list of targetComparatorOutcomes from file

createMultiThreadingSettings(): Create CohortMethod multi-threading settings

createDefaultMultiThreadingSettings(): Create default CohortMethod multi-threading settings

runCmAnalyses(): Run a list of analyses

Results of multiple analyses

Functions for viewing results of multiple analyses.

getFileReference(): Get file reference

getResultsSummary(): Get a summary report of the analyses results

getInteractionResultsSummary(): Get a summary report of the analyses results

createCmDiagnosticThresholds(): Create CohortMethod diagnostics thresholds

exportToCsv(): Export cohort method results to CSV files

getResultsDataModelSpecifications(): Get specifications for CohortMethod results data model

insertExportedResultsInSqlite(): Insert exported results into a SQLite database

launchResultsViewerUsingSqlite(): Launch Shiny app using a SQLite database

createResultsDataModel(): Create the results data model tables on a database server.

migrateDataModel(): Migrate Data model

getDataMigrator(): Get database migrations instance

uploadResults(): Upload results to the database server.

launchResultsViewer(): Launch Shiny app using

Simulation

Functions for simulating cohort method data objects.

createCohortMethodDataSimulationProfile(): Create simulation profile

simulateCohortMethodData(): Generate simulated data

cohortMethodDataSimulationProfile: A simulation profile

Helper functions

Various helper functions

checkCmInstallation(): Check is CohortMethod and its dependencies are correctly installed