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07/05/2023
Unveiling Causal Mediation Pathways in High-Dimensional Mixed Exposures: A Data-Adaptive Target Parameter Strategy
Mediation analysis in causal inference typically concentrates on one bin...
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05/30/2023
Transfer Learning With Efficient Estimators to Optimally Leverage Historical Data in Analysis of Randomized Trials
Randomized controlled trials (RCTs) are a cornerstone of comparative eff...
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05/03/2023
Semi-Parametric Identification and Estimation of Interaction and Effect Modification in Mixed Exposures using Stochastic Interventions
In many fields, including environmental epidemiology, researchers strive...
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02/15/2023
Cross-Validated Decision Trees with Targeted Maximum Likelihood Estimation for Nonparametric Causal Mixtures Analysis
Exposure to mixtures of chemicals, such as drugs, pollutants, and nutrie...
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12/19/2022
Prognostic Covariate Adjustment for Binary Outcomes Using Stratification
Covariate adjustment and methods of incorporating historical data in ran...
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05/22/2022
The Selectively Adaptive Lasso
Machine learning regression methods allow estimation of functions withou...
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08/14/2021
Mixed models for repeated measures should include time-by-covariate interactions to assure power gains and robustness against dropout bias relative to complete-case ANCOVA
In randomized trials with continuous-valued outcomes the goal is often t...
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06/07/2021
Multivariate Probabilistic Regression with Natural Gradient Boosting
Many single-target regression problems require estimates of uncertainty ...
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04/21/2021
Designing efficient randomized trials: power and sample size calculation when using semiparametric efficient estimators
Trials enroll a large number of subjects in order to attain power, makin...
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12/24/2020
Bayesian prognostic covariate adjustment
Historical data about disease outcomes can be integrated into the analys...
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12/17/2020
Increasing the efficiency of randomized trial estimates via linear adjustment for a prognostic score
Estimating causal effects from randomized experiments is central to clin...
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06/02/2020
Performance metrics for intervention-triggering prediction models do not reflect an expected reduction in outcomes from using the model
Clinical researchers often select among and evaluate risk prediction mod...
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05/29/2020
A Causal Machine Learning Framework for Predicting Preventable Hospital Readmissions
Clinical predictive algorithms are increasingly being used to form the b...
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10/08/2019
NGBoost: Natural Gradient Boosting for Probabilistic Prediction
We present Natural Gradient Boosting (NGBoost), an algorithm which bring...
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04/14/2018
General-purpose validation and model selection when estimating individual treatment effects
Practitioners in medicine, business, political science, and other fields...
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10/31/2017
Synth-Validation: Selecting the Best Causal Inference Method for a Given Dataset
Many decisions in healthcare, business, and other policy domains are mad...
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07/01/2017