Non-plug-in estimators could outperform plug-in estimators: a cautionary note and a diagnosis

Cites Work

Unnamed Item
Asymptotic expansions for general statistical models. With the assist. of W. Wefelmeyer
On asymptotically efficient estimation in semiparametric models
Estimation in semiparametric models. Some recent developments
Interval estimation for a binomial proportion. (With comments and a rejoinder).
Targeted learning in data science. Causal inference for complex longitudinal studies
Weak convergence and empirical processes. With applications to statistics
Bayesian and frequentist regression methods
Estimating effects with rare outcomes and high dimensional covariates: knowledge is power
Statistical Analysis of Financial Data in S-Plus
Estimation of Regression Coefficients When Some Regressors Are Not Always Observed
On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects
Analysis of Semiparametric Regression Models for Repeated Outcomes in the Presence of Missing Data
Conformal Inference of Counterfactuals and Individual Treatment Effects
Double/debiased machine learning for treatment and structural parameters
Super Learner
Prediction sets adaptive to unknown covariate shift
Evaluating the robustness of targeted maximum likelihood estimators via realistic simulations in nutrition intervention trials
Double robust efficient estimators of longitudinal treatment effects: comparative performance in simulations and a case study
Targeted maximum likelihood learning
A targeted maximum likelihood estimator of a causal effect on a bounded continuous outcome
Targeted minimum loss based estimation of a causal effect on an outcome with known conditional bounds

This page was built for publication: Non-plug-in estimators could outperform plug-in estimators: a cautionary note and a diagnosis