4 papers
Calibrated sensitivity models
Alec McClean, Zach Branson, Edward H. Kennedy
In causal inference, sensitivity models assess how unmeasured confounders could alter causal analyses, but the sensitivity parameter -- which quantifies the degree of unmeasured co…
Longitudinal weighted and trimmed treatment effects with flip interventions
Alec McClean, Alexander W. Levis, Nicholas Williams +1
Weighting and trimming are popular methods for addressing positivity violations in causal inference. While well-studied with single-timepoint data, standard methods do not easily g…
Double Cross-fit Doubly Robust Estimators: Beyond Series Regression
Alec McClean, Sivaraman Balakrishnan, Edward H. Kennedy +1
Doubly robust estimators with cross-fitting have gained popularity in causal inference due to their favorable structure-agnostic error guarantees. However, when additional structur…
Stochastic interventions, sensitivity analysis, and optimal transport
Alexander W. Levis, Edward H. Kennedy, Alec McClean +2
Recent methodological research in causal inference has focused on effects of stochastic interventions, which assign treatment randomly, often according to subject-specific covariat…