2021
- - Causal inference with latent variables for unmeasured confounding
- - Causal mediation analysis for exposure mixtures
- - Data-adaptively learning strata-specific causal effects
- - Tuning the highly adaptive lasso estimator
- - Applying targeted learning to improve global health equity
- - Machine learning for conditional density estimation
- - TMLE of a treatment-specific multivariate survival curve
- - Conditions for asymptotic efficiency of TMLE
- - Causal inference with left-censoring and left-truncation
- - Stochastic treatment regimes in practice
- - Feature engineering with large datasets
- - Super learning and interaction terms in models
- - Adaptive designs with continuous treatments
2020
2019
- - Two-stage sampling and survival analysis
- - Simultaneous inference with the Kaplan-Meier estimator of survival
- - Positivity assumption violations and TMLE for longitudinal data with many time-varying covariates
- - Longitudinal causal model under obscured time-ordering
- - Estimating the sample average treatment effect under effect modification in a cluster randomized trial
- - CV-TMLE and double machine learning
- - Prediction intervals using the TMLE framework
- - Applications of TMLE in infectious disease research
- - Adaptive algorithm selection via the Super Learner
- - TMLE versus the one-step estimator
- - Imputation and missing data in the TMLE framework
2018
2017
