| madr.mcmc {madr} | R Documentation |
Calculate model averaged double robust estimate using a pseudo-MC3 algorithm
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 |