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arxiv: 2210.04681 · v2 · pith:PDJR25T2new · submitted 2022-10-10 · 📊 stat.ME · math.ST· stat.TH

Sensitivity Analysis for Marginal Structural Models

Matteo Bonvini , Edward Kennedy , Valerie Ventura , Larry Wasserman This is my paper
classification 📊 stat.ME math.STstat.TH
keywords confoundingmodelmodelssensitivitymarginalstructuralunmeasuredallow
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We introduce several methods for assessing sensitivity to unmeasured confounding in marginal structural models; importantly we allow treatments to be discrete or continuous, static or time-varying. We consider three sensitivity models: a propensity-based model, an outcome-based model, and a subset confounding model, in which only a fraction of the population is subject to unmeasured confounding. In each case we develop efficient estimators and confidence intervals for bounds on the causal parameters.

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