R: Causal Effect Estimation via Doubly Robust One-Step Estimators and TMLE in Graphical Models with Unmeasured Variables

# Causal Effect Estimation via Doubly Robust One-Step Estimators and TMLE in Graphical Models with Unmeasured Variables

## Documentation for package ‘flexCausal’ version 0.1.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

data_backdoor | Data generated from a classic backdoor model, where the pre-treatment variable X cause A and Y, and the treatment A cause Y.
data_example_a | Data generated from the simulation model in Figure 4(a) of the paper <https://arxiv.org/abs/2409.03962>. The model can also be found in Figure (a) of the github repository: <https://github.com/annaguo-bios/flexCausal>
data_example_b | Data generated from the simulation model in Figure 4(b) of the paper <https://arxiv.org/abs/2409.03962>. The model can also be found in Figure (b) of the github repository: <https://github.com/annaguo-bios/flexCausal>
data_frontdoor | Data generated from a classic front-door model.
estADMG | Estimate the average causal effect (ACE) under an ADMG.
f.adj_matrix | Build an adjacency matrix from a graph.
f.children | Get the children of a node OR nodes in a graph.
f.descendants | Get the descendants of a node OR nodes in a graph.
f.district | Get the district of a vertex in a graph.
f.markov_blanket | Get the Markov blanket of a vertex in a graph.
f.markov_pillow | Get the Markov pillow of a vertex in a graph.
f.parents | Get the parents of a node OR nodes in a graph.
f.reachable_closure | Reachable closure of a set of vertices in a graph.
f.top_order | Get the topological ordering of a graph from a graph object.
is.fix | Fixability of a treatment variable in a graph.
is.mb.shielded | Check if a graph is mb-shielded.
is.np.saturated | Check if a graph is nonparametrically saturated.
is.p.fix | Primal fixability of a treatment variable in a graph.
make.graph | Create graph object.