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madr (version 1.0.0)

Model Averaged Double Robust Estimation

Description

Estimates average treatment effects using model average double robust (MA-DR) estimation. The MA-DR estimator is defined as weighted average of double robust estimators, where each double robust estimator corresponds to a specific choice of the outcome model and the propensity score model. The MA-DR estimator extend the desirable double robustness property by achieving consistency under the much weaker assumption that either the true propensity score model or the true outcome model be within a specified, possibly large, class of models.

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Version

Install

install.packages('madr')

Monthly Downloads

147

Version

1.0.0

License

GPL-3

Maintainer

Matthew Cefalu

Last Published

September 5th, 2016

Functions in madr (1.0.0)

add.to.dictionary

Worker function that fits propensity score models
expit

Expit (inverse logit) function
add.to.dictionary.outcome

Worker function that fits outcome models
print.madr.enumerate

Print function for madr.enumerate class
madr.enumerate

Model averaged double robust estimate with enumeration of all possible models (linear terms only)
OM.MA

Calculate model probabilities for the outcome models using a pseudo-MC3 algorithm
bic.to.prob

Convert BIC to model probabilities
madr

Calculate model averaged double robust estimate
madr.mcmc

Calculate model averaged double robust estimate using a pseudo-MC3 algorithm
OM.MA.enumerate

Enumerates all possible outcome models (linear terms only)
print.madr.mcmc

Print function for madr.mcmc class
PS.MA.enumerate

Enumerates all possible propensity score models (linear terms only)
print.summary.madr.enumerate

Print function for summary.madr.enumerate class
summary.madr.enumerate

Provides model averaged double robust estimate for different values of tau
PS.MA

Calculate model probabilities for the propensity score model using a pseudo-MC3 algorithm