# Non-parametric causal effects based on longitudinal modified treatment policies

@article{Diaz2020NonparametricCE,
title={Non-parametric causal effects based on longitudinal modified treatment policies},
author={Iv'an D'iaz and Nicholas Williams and Katherine L. Hoffman and Edward J. Schenck},
journal={arXiv: Methodology},
year={2020}
}
Most causal inference methods consider counterfactual variables under interventions that set the treatment deterministically. With continuous or multi-valued treatments or exposures, such counterfactuals may be of little practical interest because no feasible intervention can be implemented that would bring them about. Furthermore, violations to the positivity assumption, necessary for identification, are exacerbated with continuous and multi-valued treatments and deterministic interventions…

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