Questions tagged [doubly-robust-estimator]

The tag has no usage guidance.

Filter by
Sorted by
Tagged with
5
votes
0answers
97 views

Derivation of a doubly robust estimator with clever covariate and inverse probability weighting

With notation: outcome $Y$, (binary) treatment $A$, and covariates $L$. In Hernan and Robins (2020) causal inference textbook: To obtain a doubly robust estimate of the average causal effect, first ...
0
votes
1answer
28 views

Doubly robust learning with binary treatment and outcome

I'm trying to use doubly robust learning to estimate heterogenous treatment effects. My treatments T and outcomes y are both binary. I'm following the example listed under "How do I select the ...
1
vote
0answers
19 views

Doubly robust learning with same features influencing treatment and outcome

I'm looking at some of the examples in the econML package for double machine learning. Specifically, the example found here (code below). In the example W is the features which might influence both ...
3
votes
1answer
113 views

Is the emmeans R package performing causal inference G-computation?

So I am trying to get an understanding of causal inference and how it differs from the usual contrasts. I regularly use the emmeans package in R, and I am wondering when the function emmeans() ...
1
vote
0answers
25 views

Evaluation metrics for an RL model. How to select then?

I trained an RL model adapting the RL batch example (Jupyter Notebook) to the problem I was aiming to solve. As for the training, everything went well but, even though the RL batch returned several ...
1
vote
0answers
63 views

Doubly Robust Estimator

When use Doubly Robust Estimator we train m0/m1 models and propensity score model to be used by the estimator. Is it OK to use the same dataset to train those models and then use them to measure ATE ...
2
votes
0answers
86 views

Variance for a doubly-robust CATE estimator

I am interested in how the variance for the conditional average treatment effect (CATE) is calculated for the doubly robust pseudo-outcome approach. Below are the exact details of the problem and my ...
2
votes
1answer
63 views

Problem to implement Bang & Robins double robust estimator

I have a question with regard to the implementation of Bang & Robins (2005) double robust estimator of a treatment effect (formula at the bottom of page 964). The idea of their estimator is to ...
5
votes
1answer
649 views

Theory behind Targeted Maximum Likelihood Estimation (TMLE)

There are many fine how-to articles describing how to implement TMLE but they avoid the details of the underlying theory. I'm currently working my way through Targeted Learning: Causal Inference for ...
2
votes
1answer
185 views

Does a doubly robust estimator magnify bias if *both* the outcome regression and inverse propensity score weighting are incorrect models?

The doubly robust estimator is a popular method for measuring the average treatment effect with observational data (assuming no unmeasured confounders): $$ \hat{\Delta}_{DR} = n^{-1}\sum_{i=1}^n \...