bal.stat: Calculate weighted balance statistics

Description

`bal.stat` compares the treatment and control subjects by means, standard deviations, effect size, and KS statistics

Usage

bal.stat(
  data,
  vars = NULL,
  treat.var,
  w.all,
  sampw,
  get.means = TRUE,
  get.ks = TRUE,
  na.action = "level",
  estimand,
  multinom,
  fillNAs = FALSE
)

Value

`get.means` and `get.ks` manipulate the inclusion of certain columns in the returned result.

Arguments

data: A data frame containing the data
vars: A vector of character strings with the names of the variables on which the function will assess the balance
treat.var: The name of the treatment variable
w.all: Oobservation weights (e.g. propensity score weights, sampling weights, or both)
sampw: Sampling weights. These are passed in addition to `w.all` because the "unweighted" results shoud be adjusted for sample weights (though not propensity score weights).
get.means: logical. If `TRUE` then `bal.stat` will compute means and variances
get.ks: logical. If `TRUE` then `bal.stat` will compute KS statistics
na.action: A character string indicating how `bal.stat` should handle missing values. Current options are "level", "exclude", or "lowest"
estimand: Either "ATT" or "ATE"
multinom: logical. `TRUE` if used for multinomial propensity scores.
fillNAs: logical. If `TRUE`, fills in zeros for missing values.

Details

`bal.stat` calls auxiliary functions for each variable and assembles the results in a table.

References