For every covariate, prevalence in treatment and comparator groups before and after matching/trimming are computed. When variable ratio matching was used the balance score will be corrected according the method described in Austin et al (2008).

computeCovariateBalance(population, cohortMethodData,
  subgroupCovariateId = NULL)

Arguments

population

A data frame containing the people that are remaining after matching and/or trimming.

cohortMethodData

An object of type cohortMethodData as generated using getDbCohortMethodData.

subgroupCovariateId

Optional: a covariate ID of a binary covariate that indicates a subgroup of interest. Both the before and after populations will be restricted to this subgroup before computing covariate balance.

Value

Returns a date frame describing the covariate balance before and after matching/trimming.

Details

The population data frame should have at least the following columns:

rowId(integer)A unique identifier for each row (e.g. the person ID)
treatment(integer)Column indicating whether the person is in the target (1) or comparator (0)
group

References

Austin, P.C. (2008) Assessing balance in measured baseline covariates when using many-to-one matching on the propensity-score. Pharmacoepidemiology and Drug Safety, 17: 1218-1225.