9 citations · 24 across the 4 of their papers we have counts for
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Robust inference on the average treatment effect using the outcome highly adaptive lasso
Cheng Ju, David Benkeser, Mark J. van der Laan
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 fl…
Collaborative targeted inference from continuously indexed nuisance parameter estimators
Cheng Ju, Antoine Chambaz, Mark J. van der Laan
We wish to infer the value of a parameter at a law from which we sample independent observations. The parameter is smooth and we can define two variation-independent features of th…
On Adaptive Propensity Score Truncation in Causal Inference
Cheng Ju, Joshua Schwab, Mark J. van der Laan
The positivity assumption, or the experimental treatment assignment (ETA) assumption, is important for identifiability in causal inference. Even if the positivity assumption holds,…
Collaborative-controlled LASSO for Constructing Propensity Score-based Estimators in High-Dimensional Data
Cheng Ju, Richard Wyss, Jessica M. Franklin +3
Propensity score (PS) based estimators are increasingly used for causal inference in observational studies. However, model selection for PS estimation in high-dimensional data has…