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. An object of type cohortMethodData as generated using getDbCohortMethodData. 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.