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:
install.packages("remotes")
remotes::install_github("ohdsi/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.