SelfControlledCaseSeries is part of the OHDSI Methods Library.
SelfControlledCaseSeries is an R package for performing Self-Controlled Case Series (SCCS) analyses in an observational database in the OMOP Common Data Model.
- Extracts the necessary data from a database in OMOP Common Data Model format.
- Optionally add seasonality using a spline function.
- Optionally add age using a spline function.
- Optionally correct for event-dependent censoring of the observation period.
- Optionally add many covariates in one analysis (e.g. all drugs).
- Options for constructing different types of covariates and risk windows, including pre-exposure windows (to capture contra-indications).
- Optionally use regularization on all covariates except the outcome of interest.
sccsData <- getDbSccsData(connectionDetails = connectionDetails, cdmDatabaseSchema = cdmDatabaseSchema, outcomeIds = 192671, exposureIds = 1124300) covarDiclofenac = createCovariateSettings(label = "Exposure of interest", includeCovariateIds = 1124300, start = 0, end = 0, addExposedDaysToEnd = TRUE) sccsEraData <- createSccsEraData(sccsData, naivePeriod = 180, firstOutcomeOnly = FALSE, covariateSettings = covarDiclofenac) model <- fitSccsModel(sccsEraData) summary(model) # sccsModel object summary # # Outcome ID: 192671 # # Outcome count: # Event count Case count # 192671 433433 137888 # # Estimates: # Name ID Estimate lower .95 upper .95 logRr seLogRr # Exposure of interest: Diclofenac 1000 1.274 1.213 1.336 0.2421 0.02431
SelfControlledCaseSeries is an R package, with some functions implemented in C++.
Requires R (version 3.2.2 or higher). Installation on Windows requires RTools. Libraries used in SelfControlledCaseSeries require Java.
- On Windows, make sure RTools is installed.
- The DatabaseConnector and SqlRender packages require Java. Java can be downloaded from http://www.java.com.
- In R, use the following commands to download and install SelfControlledCaseSeries:
install.packages("drat") drat::addRepo("OHDSI") install.packages("SelfControlledCaseSeries")
- Vignette: Single studies using the SelfControlledCaseSeries package
- Vignette: Running multiple analyses at once using the SelfControlledCaseSeries package
- Package manual: SelfControlledCaseSeries.pdf
- Developer questions/comments/feedback: OHDSI Forum
- We use the GitHub issue tracker for all bugs/issues/enhancements
SelfControlledCaseSeries is licensed under Apache License 2.0
SelfControlledCaseSeries is being developed in R Studio.
- This project is supported in part through the National Science Foundation grant IIS 1251151.
- Part of the code is based on the SCCS package by Yonas Ghebremichael-Weldeselassie, Heather Whitaker, and Paddy Farrington.