Usage
ks.stat(logw = NULL, w.ctrl = NULL,
gbm1 = NULL, i = 1, data,
sampw = rep(1, nrow(data)),
rule.summary = mean, na.action = "level",
vars, treat.var, collapse.by.var = FALSE,
verbose = FALSE)
es.stat(logw = NULL, w.ctrl = NULL,
gbm1 = NULL, i = 1, data,
sampw = rep(1, nrow(data)),
rule.summary = mean, na.action = "level",
vars, treat.var, collapse.by.var = FALSE,
verbose = FALSE)
strata.stat(logw = NULL, w.ctrl = NULL,
gbm1 = NULL, i = 1, data,
sampw = rep(1, nrow(data)),
rule.summary = mean, na.action = "level",
vars, treat.var, collapse.by.var = FALSE,
verbose = FALSE)Arguments
logw
the logarithm of the weights
w.ctrl
the weights for the control subjects
gbm1
a gbm.object used for estimating the
propensity scores, usually the gbm component of a ps
object returned from i
the iteration of gbm with which to compute the
weights data
a data frame with the data
sampw
optional sampling weights
rule.summary
a function for summarizing the total balance. Used to
collapse statistics across all the covariates. Examples
include mean and max
na.action
a string indicating the method for handling missing data
vars
a vector of variable names corresponding to data
treat.var
the name of the treatment variable
collapse.by.var
if TRUE, then statistics computed for factors
are collapsed across the levels
verbose
if TRUE, lots of information will be printed to monitor the
the progress of the fitting