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.…
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…
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…
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…