Create CohortMethod multi-threading settings
Source:R/RunAnalyses.R
createMultiThreadingSettings.Rd
Create CohortMethod multi-threading settings
Usage
createMultiThreadingSettings(
getDbCohortMethodDataThreads = 1,
createPsThreads = 1,
psCvThreads = 1,
createStudyPopThreads = 1,
trimMatchStratifyThreads = 1,
computeSharedBalanceThreads = 1,
computeBalanceThreads = 1,
prefilterCovariatesThreads = 1,
fitOutcomeModelThreads = 1,
outcomeCvThreads = 1,
calibrationThreads = 1
)
Arguments
- getDbCohortMethodDataThreads
The number of parallel threads to use for building the cohortMethod data objects.
- createPsThreads
The number of parallel threads to use for fitting the propensity models.
- psCvThreads
The number of parallel threads to use for the cross- validation when estimating the hyperparameter for the propensity model. Note that the total number of CV threads at one time could be
createPsThreads * psCvThreads
.- createStudyPopThreads
The number of parallel threads to use for creating the study population.
- trimMatchStratifyThreads
The number of parallel threads to use for trimming, matching and stratifying.
The number of parallel threads to use for computing shared covariate balance.
- computeBalanceThreads
The number of parallel threads to use for computing covariate balance.
- prefilterCovariatesThreads
The number of parallel threads to use for prefiltering covariates.
- fitOutcomeModelThreads
The number of parallel threads to use for fitting the outcome models.
- outcomeCvThreads
The number of parallel threads to use for the cross- validation when estimating the hyperparameter for the outcome model. Note that the total number of CV threads at one time could be
fitOutcomeModelThreads * outcomeCvThreads
.- calibrationThreads
The number of parallel threads to use for empirical calibration.