This function fits outcome models and saves necessary information
add.to.dictionary.outcome(Y, X, U, W, alpha, binary = F)
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)
alpha: vector of inclusion indicators (which columns of U) to included in the propensity score model
binary: indicates if the outcome is binary
Returns
A list. The list contains the following named components: - out: a list that contains the BIC, predicted values, and estimated treatment effect from each outcome model