3 papers
stat.ME2026
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.…
stat.ME2026
Causal Inference with Missing Exposures and Missing Outcomes
Kirsten E. Landsiedel, Rachel Abbott, Atukunda Mucunguzi +6
Missing data are ubiquitous in public health research. When estimating causal effects, there are well-established methods to address bias to due missing outcomes. Commonly, causal…
stat.ME2025
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…