4 papers · 1 filter
Targeted maximum likelihood estimation for longitudinal two-stage designs with outcome subsampling
Kirsten E. Landsiedel, Maya L. Petersen, Mark J. van der Laan
We consider efficient estimation of causal parameters in longitudinal two-stage designs with outcome subsampling, motivated by resampling designs in HIV-related mortality studies.…
An Online Meta-Level Adaptive Design Framework with Targeted Learning Inference: Applications to Evaluating and Utilizing Surrogate Outcomes in Adaptive Designs
Wenxin Zhang, Aaron Hudson, Maya Petersen +1
Adaptive designs are increasingly used in clinical trials and online experiments to improve participant outcomes by dynamically updating treatment allocation as data accumulate. In…
Hazard-Based Targeted Maximum Likelihood Estimation for Survival in Resampling Designs
Kirsten E. Landsiedel, Rachael V. Phillips, Maya L. Petersen +1
Survival is a key metric for evaluating standards of care for people living with HIV. In resource-limited settings, high rates of loss to follow-up (LTFU) often result in underesti…
The Causal Roadmap and Simulations to Improve the Rigor and Reproducibility of Real-Data Applications
Nerissa Nance, Maya L. Petersen, Mark van der Laan +1
The Causal Roadmap outlines a systematic approach to asking and answering questions of cause-and-effect: define the quantity of interest, evaluate needed assumptions, conduct stati…