# psw.aug: Propensity score weighting with augmented estimation In PSW: Propensity Score Weighting Methods for Dichotomous Treatments

## Description

psw.aug is the function to estimate the augmented estimator for mean difference (mean outcome difference for "gaussian" family and risk difference for "binomial" family). The augmented estimator is consistent for the estimand defined by the corresponding propensity score model.

## Usage

 1 psw.aug(data, form.ps, weight, form.outcome, family = "gaussian", K = 4) 

## Arguments

 data data frame to be used. form.ps propensity score model. weight weighting method to be used. Available methods are "ATE", "ATT", "ATC", "MW", "OVERLAP", and "TRAPEZOIDAL". form.outcome outcome model. family outcome family, either "gaussian" or "binomial". family="gaussian" by default. K value of K in ω(e_i) = min(1, K min(e_i, 1-e_i)) for "TRAPEZOIDAL" weight. The estimand is closer to the average treatment effect (ATE) with larger value of K. K=4 by default.

## Details

psw.aug is used to estimate the augmented estimator, \hat{Δ}_{aug}, and make inference using the sandwich variance that adjusts for the sampling variability in the estimated propensity score.

## Value

A list of weighting method, fitted propensity score model, estimated propenstity scores, estimated propensity score weights, augmented estimator and associated standard error.

 weight weighting method. ps.model object returned by fitting the propensity score model using glm with "binomial" family. ps.hat estimated propensity score. W estimated propensity score weight. est.aug augmented estimator for mean difference when family = "gaussian". std.aug standard error for est.aug. est.risk.aug augmented estimator for risk difference when family = "binomial". std.risk.aug standard error for est.risk.aug.

## Examples

 1 2 3 4 5 6 7 8 # Load the test data set data(test_data); # Propensity score model form.ps <- "Z ~ X1 + X2 + X3 + X4"; # Outcome model form.out <- "Y ~ X1 + X2 + X3 + X4"; tmp <- psw.aug( data = test_data, form.ps = form.ps, weight = "ATE", form.outcome = form.out, family="gaussian" ); 

PSW documentation built on May 2, 2019, 6:01 a.m.