Compute weights for ate estimation

alphaHatEff(Y, X, Z, Qn1, Qn0, gn, select)

Arguments

Y

The outcome

X

The covariates

Z

The binary treatment

Qn1

A matrix of predictions from SuperLearner on training data with Z = 1

Qn0

A matrix of predictions from SuperLearner on training data with Z = 0

gn

A matrix of propensity estimates in training data

select

How to choose amongst outcomes

Value

weights A numeric vector of weights of the same length as the number of outcomes considered. The weights sum to 1.