9 citations · 18 across the 16 of their papers we have counts for
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stat.ME2019
Efficient estimation of optimal regimes under a no direct effect assumption
Lin Liu, Zach Shahn, James M. Robins +1
We derive new estimators of an optimal joint testing and treatment regime under the no direct effect (NDE) assumption that a given laboratory, diagnostic, or screening test has no…
stat.ML2019★ 5 cited
On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning
Lin Liu, Rajarshi Mukherjee, James M. Robins
For many causal effect parameters of interest, doubly robust machine learning (DRML) estimators are the state-of-the-art, incorporating the good prediction performance…