madr.mcmc: Calculate model averaged double robust estimate using a...

In mcefalu/madr: Model Averaged Double Robust Estimation

Description

This function uses a pseudo-MC3 algorithm to search the model space, then estimate a model averaged double robust estimate using the two-stage procedure for estimating model weights with tau=0.

Usage

madr.mcmc(Y, X, U, W = NULL, M = 1000, cut = 0.95)

Arguments

Y	vector of the outcome
X	vector of the treatment (0/1)
U	matrix of covariates to be considered for inclusion/exclusion
W	matrix of covariates that will be included in all models (optional)
M	the number of MCMC iteration
cut	cumulative probability of models to be retained for improved computational efficiency (1 retains all visited models)

Value

A list. The list contains the following named components:

madr	the model averaged double robust estimate
weight.ps	a vector that contains the inclusion probability of each covariate in the propensity score model
weight.om	a vector that contains the inclusion probability of each covariate in the outcome model

mcefalu/madr documentation built on May 22, 2019, 3 p.m.