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08/28/2023
Data fusion using weakly aligned sources
We introduce a new data fusion method that utilizes multiple data source...
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07/24/2023
Adaptive debiased machine learning using data-driven model selection techniques
Debiased machine learning estimators for nonparametric inference of smoo...
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03/29/2023
One-Step Estimation of Differentiable Hilbert-Valued Parameters
We present estimators for smooth Hilbert-valued parameters, where smooth...
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02/27/2023
Causal isotonic calibration for heterogeneous treatment effects
We propose causal isotonic calibration, a novel nonparametric method for...
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10/31/2022
Can the potential benefit of individualizing treatment be assessed using trial summary statistics alone?
Individualizing treatment assignment can improve outcomes for diseases w...
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03/03/2022
A general adaptive framework for multivariate point null testing
As a common step in refining their scientific inquiry, investigators are...
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01/18/2022
Individualized treatment rules under stochastic treatment cost constraints
Estimation and evaluation of individualized treatment rules have been st...
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12/21/2021
Efficient Estimation of the Maximal Association between Multiple Predictors and a Survival Outcome
This paper develops a new approach to post-selection inference for scree...
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12/21/2021
Improved Efficiency for Cross-Arm Comparisons via Platform Designs
Though platform trials have been touted for their flexibility and stream...
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11/29/2021
Efficient Estimation Under Data Fusion
We aim to make inferences about a smooth, finite-dimensional parameter b...
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07/24/2021
Improved inference for vaccine-induced immune responses via shape-constrained methods
We study the performance of shape-constrained methods for evaluating imm...
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06/11/2021
Inference for treatment-specific survival curves using machine learning
In the absence of data from a randomized trial, researchers often aim to...
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04/30/2021
Estimating the Efficiency Gain of Covariate-Adjusted Analyses in Future Clinical Trials Using External Data
We present a general framework for using existing data to estimate the e...
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12/10/2020
Leveraging vague prior information in general models via iteratively constructed Gamma-minimax estimators
Gamma-minimax estimation is an approach to incorporate prior information...
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10/09/2020
Discussion of Kallus (2020) and Mo, Qi, and Liu (2020): New Objectives for Policy Learning
We discuss the thought-provoking new objective functions for policy lear...
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09/13/2020
Sufficient and insufficient conditions for the stochastic convergence of Cesàro means
We study the stochastic convergence of the Cesàro mean of a sequence of ...
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03/04/2020
Universal sieve-based strategies for efficient estimation using machine learning tools
Suppose that we wish to estimate a finite-dimensional summary of one or ...
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02/26/2020
