Returns the mean and standardized mean associated with each treatment group,
before and after weighting. To access more comprehensive diagnotistics for
assessing covariate balance, consider using Noah Greifer's cobalt package.
Usage
balance(object, ...)
Value
Returns a list of two matrices, "original" (before weighting) and
"balanced" (after weighting).
Arguments
object
A CBPS, npCBPS, or CBMSM object.
...
Additional arguments to be passed to balance.
Author
Christian Fong, Marc Ratkovic, and Kosuke Imai.
Details
For binary and multi-valued treatments as well as marginal structural
models, each of the matrices' rows are the covariates and whose columns are
the weighted mean, and standardized mean associated with each treatment
group. The standardized mean is the weighted mean divided by the standard
deviation of the covariate for the whole population. For continuous
treatments, returns the absolute Pearson correlation between the treatment
and each covariate.