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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.ME2024
Causal Inference in Randomized Trials with Partial Clustering
Joshua Nugent, Elijah Kakande, Gabriel Chamie +5
Clustering and dependence are common in trials. For example, in some cluster randomized trials (CRTs), pre-existing clusters are enrolled, randomized, and serve as the basis of int…