Selective machine learning of doubly robust functionals
Y Cui, EJ Tchetgen Tchetgen - Biometrika, 2024 - academic.oup.com
While model selection is a well-studied topic in parametric and nonparametric regression or
density estimation, selection of possibly high-dimensional nuisance parameters in …
density estimation, selection of possibly high-dimensional nuisance parameters in …
Robust inference on the average treatment effect using the outcome highly adaptive lasso
Many estimators of the average effect of a treatment on an outcome require estimation of the
propensity score, the outcome regression, or both. It is often beneficial to utilize flexible …
propensity score, the outcome regression, or both. It is often beneficial to utilize flexible …
[PDF][PDF] Flexible collaborative estimation of the average causal effect of a treatment using the outcome‐highly‐adaptive Lasso
Many estimators of the average causal effect of an intervention require estimation of the
propensity score, the outcome regression, or both. For these estimators, we must carefully …
propensity score, the outcome regression, or both. For these estimators, we must carefully …
[图书][B] Variable and Model Selection for Propensity Score Estimators in Causal Inference
C Ju - 2018 - search.proquest.com
Robust inference of a low-dimensional parameter in a large semi-parametric model relies on
external estimators of infinite-dimensional features of the distribution of the data. Typically …
external estimators of infinite-dimensional features of the distribution of the data. Typically …