twang (version 1.2-5)

dx.wts: Propensity score diagnostics

Description

dx.wts takes a ps object or a set of propensity scores and computes diagnostics assessing covariates balance.

Usage

dx.wts(x,
       data,
       estimand,
       vars=NULL,
       treat.var,
       x.as.weights=TRUE,
       sampw=NULL,
       perm.test.iters=0)

Arguments

x

a data frame, matrix, or vector of propensity score weights or a ps object. x can also be a data frame, matrix, or vector of propensity scores if x.as.weights=FALSE

data

a data frame

estimand

the estimand of interest: either "ATT" or "ATE"

vars

a vector of character strings naming variables in data on which to assess balance

treat.var

a character string indicating which variable in data contains the 0/1 treatment group indicator

x.as.weights

TRUE or FALSE indicating whether x specifies propensity score weights or propensity scores. Ignored if x is a ps object

sampw

optional sampling weights. If x is a ps object then the sampling weights should have been passed to ps and not specified here. dx.wts will issue a warni

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

Value

• Returns a list containing
• treat
  the vector of 0/1 treatment assignment indicators
• desc
  a nested list containing detailed diagnostic information on the weights. This includes the number of treatment and control subjects, the effective sample size, the largest KS statistic, the average absolute effect size, and the complete balance table
• summary.tab
  a data frame showing balance information
• ps
  the given propensity scores
• w
  the given weights
• datestamp
  the date and time of the call to dx.wts
• parameters
  the parameters used when calling dx.wts
• alerts
  text containing any warnings accumulated during the estimation
• varNames
  the variable names

Details

Creates a balance table that compares unweighted and weighted means and standard deviations, computes effect sizes, and KS statistics to assess the ability of the propensity scores to balance the treatment and control groups.

See Also

The example for ps contains an example of the use of dx.wts