Software Open Access
tmle3shift: Targeted Learning of the Causal Effects of Stochastic Shift Interventions
Hejazi, Nima S;
Coyle, Jeremy R;
van der Laan, Mark J
tmle3shift is an adapter/extension R package in the tlverse ecosystem that exposes support for the estimation of a target parameter defined as the mean counterfactual outcome under a shift of the natural value of a continuous-valued intervention. The package provides tools for targeted maximum likelihood estimation (TMLE) of the population-level causal effects of stochastic treatment regimes characterized as modified treatment policies and related nonparametric variable importance analyses.
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tmle3shift_0.2.0.tar.gz
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Indexed in
- Publication date:
- March 13, 2021
- DOI:
-
- Keyword(s):
- targeted learning causal inference causal machine learning stochastic treatment regime stochastic intervention
- License (for files):
- GNU General Public License v3.0 only