mean_est function

The Inverse Probability Weighted Estimator of the Marginal Mean Given a Specific Treatment Regime

Estimate the marginal mean of the response when the entire population follows a treatment regime. This function implements the inverse probability weighted estimator proposed by Baqun Zhang et. al..

This function supports the mestimate function.

mean_est(beta, x, a, y, prob)

Arguments

• beta: a vector indexing the treatment regime. It indexes a linear treatment regime:

• x: a matrix of observed covariates from the sample. Notice that we assumed the class of treatment regimes is linear. This is important that columns in x matches with beta.
• a: a vector of 0s and 1s, the observed treatments from a sample
• y: a vector, the observed responses from a sample
• prob: a vector, the propensity scores of getting treatment 1 in the samples

References

Rdpack::insert_ref(key="zhang2012robust",package="quantoptr")