SelfControlledCaseSeries is part of HADES.
SelfControlledCaseSeries is an R package for performing Self-Controlled Case Series (SCCS) analyses in an observational database in the OMOP Common Data Model.
sccsData <- getDbSccsData(connectionDetails = connectionDetails, cdmDatabaseSchema = cdmDatabaseSchema, outcomeIds = 192671, exposureIds = 1124300) studyPop <- createStudyPopulation(sccsData = sccsData, outcomeId = 192671, firstOutcomeOnly = FALSE, naivePeriod = 180) covarDiclofenac = createEraCovariateSettings(label = "Exposure of interest", includeEraIds = 1124300, start = 0, end = 0, endAnchor = "era end") sccsIntervalData <- createSccsIntervalData(studyPop, sccsData, eraCovariateSettings = covarDiclofenac) model <- fitSccsModel(sccsIntervalData) model # SccsModel object # # Outcome ID: 192671 # # Outcome count: # outcomeSubjects outcomeEvents outcomeObsPeriods # 192671 272243 387158 274449 # # Estimates: # # A tibble: 1 x 7 # Name ID Estimate LB95CI UB95CI logRr seLogRr # <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> # 1 Exposure of interest: Diclofenac 1000 1.18 1.13 1.24 0.167 0.0230
Requires R (version 4.0.0 or higher). Installation on Windows requires RTools. Libraries used in SelfControlledCaseSeries require Java.
See the instructions here for configuring your R environment, including Java.
In R, use the following commands to download and install SelfControlledCaseSeries:
Documentation can be found on the package website.
PDF versions of the documentation are also available:
Read here how you can contribute to this package.
SelfControlledCaseSeries is being developed in R Studio.