Name: IcTemporalPatternDiscovery
Owner: Observational Health Data Sciences and Informatics
Description: An R package for performing the IC Temporal Pattern Discovery method.
Created: 2014-12-22 23:33:26.0
Updated: 2017-04-13 08:34:09.0
Pushed: 2017-07-05 05:14:47.0
Size: 320
Language: R
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This R package is an implementation of the IC Temporal Pattern Discovery method to estimate risk by combining a self-controlled and cohort design. It is designed to run against observational databases in the OMOP Common Data Model.
ary(SelfControlledCohort)
ectionDetails <- createConnectionDetails(dbms = "postgresql",
user = "joe",
password = "secret",
server = "myserver")
sureOutcomePairs = data.frame(outcomeId = c(196794, 196794, 312648),
exposurId = c(1501700, 1545958, 1551803))
dData <- getDbIctpdData(connectionDetails,
cdmDatabaseSchema = "cdm_schema.dbo",
exposureOutcomePairs = exposureOutcomePairs)
dResults <- calculateStatisticsIC(ictpdData)
dResults
IcTemporalPatternDiscovery is an R package.
Requires R (version 3.1.0 or higher). Libraries used in this package require Java.
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 IcTemporalPatternDiscovery:
all.packages("devtools")
ary(devtools)
all_github("ohdsi/OhdsiRTools")
all_github("ohdsi/SqlRender")
all_github("ohdsi/DatabaseConnector")
all_github("ohdsi/IcTemporalPatternDiscovery")
IcTemporalPatternDiscovery is licensed under Apache License 2.0
IcTemporalPatternDiscovery is being developed in R Studio.
Alpha
This package was developed by Tomas Bergvall, adapted by Martijn Schuemie.