R: Diagnosis of weights

desc.wts {twang}

R Documentation

Diagnosis of weights

Description

desc.wts assesses the quality of a set of weights on balancing a treatment and control group.

Usage

desc.wts(data, 
         w, 
         sampw = sampw,
         vars = NULL, 
         treat.var, 
         tp, 
         na.action = "level",
         perm.test.iters=0,
         verbose=TRUE,
         alerts.stack,
         estimand, multinom = FALSE, fillNAs = FALSE)

Arguments

`data`	a data frame containing the dataset
`w`	a vector of weights equal to `nrow(data)`
`sampw`	sampling weights, if provided
`vars`	a vector of variable names corresponding to `data`
`treat.var`	the name of the treatment variable
`tp`	a title for the method “type" used to create the weights, used to label the results
`na.action`	a string indicating the method for handling missing data
`perm.test.iters`	an non-negative integer giving the number of iterations of the permutation test for the KS statistic. If `perm.test.iters=0` then the function returns an analytic approximation to the p-value. This argument is ignored is `x` is a `ps` object. Setting `perm.test.iters=200` will yield precision to within 3% if the true p-value is 0.05. Use `perm.test.iters=500` to be within 2%
`verbose`	if TRUE, lots of information will be printed to monitor the the progress of the fitting
`alerts.stack`	an object for collecting warnings issued during the analyses
`estimand`	the estimand of interest: either "ATT" or "ATE"
`multinom`	Indicator that weights are from a propsensity score analysis with 3 or more treatment groups.
`fillNAs`	If `TRUE` fills NAs with zeros.

Details

desc.wts calls bal.stat to assess covariate balance. If perm.test.iters>0 it will call bal.stat multiple times to compute Monte Carlo p-values for the KS statistics and the maximum KS statistic. It assembles the results into a list object, which usually becomes the desc component of ps objects that ps returns.

Value