The paper introduces counterfactual strata effects to identify causal estimands under missing exposures, missing baseline outcomes, and missing follow-up outcomes, demonstrated on the SEARCH-TB study with TMLE and Super Learner.
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The paper introduces a question-driven framework and set of statistical methods for exploratory assessment of regional treatment effect heterogeneity in multi-regional clinical trials, evaluated via simulations under no-heterogeneity and modifier-driven scenarios.
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Causal Inference with Missing Exposures and Missing Outcomes
The paper introduces counterfactual strata effects to identify causal estimands under missing exposures, missing baseline outcomes, and missing follow-up outcomes, demonstrated on the SEARCH-TB study with TMLE and Super Learner.
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A Workflow for Evaluating Regional Treatment Effect Heterogeneity in Multi-Regional Clinical Trials
The paper introduces a question-driven framework and set of statistical methods for exploratory assessment of regional treatment effect heterogeneity in multi-regional clinical trials, evaluated via simulations under no-heterogeneity and modifier-driven scenarios.