Module model 

DML models with linear scores: Plr, Irm, Pliv, and the LinearScoreModel trait for adding your own.

Structs

Irm

IRM estimator: ml_g learns E[Y | D = d, X] (fitted separately on the treated and control rows of each training fold), ml_m learns the propensity score P(D = 1 | X).

Pliv

PLIV estimator with the partialling-out score ψ = (Y − ℓ(X) − θ(D − r(X)))·(Z − m(X)).

Plr

PLR estimator: ml_l learns E[Y | X], ml_m learns E[D | X], and the optional ml_g learns g(X) for the IV-type score.

ScoreEstimate

Score elements plus the cross-fitted nuisance predictions behind them.

ScoreInput

The data a model sees when estimating the effect of one treatment.

Enums

IrmScore

Target parameter of Irm.

PlrScore

Orthogonal score used by Plr.

Traits

LinearScoreModel

A DML model whose orthogonal score is linear in θ.