# Identification of Causal Effects Within Principal Strata Using Auxiliary Variables

@article{Jiang2020IdentificationOC, title={Identification of Causal Effects Within Principal Strata Using Auxiliary Variables}, author={Zhichao Jiang and P. Ding}, journal={arXiv: Methodology}, year={2020} }

In causal inference, principal stratification is a framework for dealing with a posttreatment intermediate variable between a treatment and an outcome, in which the principal strata are defined by the joint potential values of the intermediate variable. Because the principal strata are not fully observable, the causal effects within them, also known as the principal causal effects, are not identifiable without additional assumptions. Several previous empirical studies leveraged auxiliary… Expand

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Multiply robust estimation of causal effects under principal ignorability.

- Mathematics, Computer Science
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