Usage
bal.stat(data,
vars = NULL,
treat.var,
w.all,
sampw,
get.means = TRUE,
get.ks = TRUE,
na.action = "level",
estimand,
multinom)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
observation 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
TRUE if used for multinomial propensity scores.