bal.stat: Calculate weighted balance statistics

In twang: Toolkit for Weighting and Analysis of Nonequivalent Groups

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
)

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.

Value

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

References

Dan McCaffrey, G. Ridgeway, Andrew Morral (2004). "Propensity Score Estimation with Boosted Regression for Evaluating Adolescent Substance Abuse Treatment", *Psychological Methods* 9(4):403-425.

See Also

The example for [ps] contains an example of the use of [bal.table]

twang documentation built on Oct. 25, 2021, 5:08 p.m.