# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "flexCausal" in publications use:' type: software license: GPL-3.0-only title: 'flexCausal: Causal Effect Estimation via Doubly Robust One-Step Estimators and TMLE in Graphical Models with Unmeasured Variables' version: 0.1.0 identifiers: - type: doi value: 10.32614/CRAN.package.flexCausal abstract: Provides doubly robust one-step and targeted maximum likelihood (TMLE) estimators for average causal effects in acyclic directed mixed graphs (ADMGs) with unmeasured variables. Automatically determines whether the treatment effect is identified via backdoor adjustment or the extended front-door functional, and dispatches to the appropriate estimator. Supports incorporation of machine learning algorithms via 'SuperLearner' and cross-fitting for nuisance estimation. Methods are described in Guo and Nabi (2024) . authors: - family-names: Guo given-names: Anna email: guo.anna617@gmail.com preferred-citation: type: article title: 'Average Causal Effect Estimation in DAGs with Hidden Variables: Extensions of Back-Door and Front-Door Criteria' authors: - family-names: Guo given-names: Anna email: guo.anna617@gmail.com - family-names: Nabi given-names: Razieh journal: arXiv preprint arXiv:2409.03962 year: '2024' url: http://arxiv.org/abs/2409.03962 repository: https://annaguo-bios.r-universe.dev repository-code: https://github.com/annaguo-bios/flexCausal commit: 229d80365c3e6500a36c55a686baae5c0b1fa433 url: https://github.com/annaguo-bios/flexCausal date-released: '2026-03-18' contact: - family-names: Guo given-names: Anna email: guo.anna617@gmail.com references: - type: article title: Flexible Nonparametric Inference for Causal Effects under the Front-Door Model authors: - family-names: Guo given-names: Anna - family-names: Benkeser given-names: David - family-names: Nabi given-names: Razieh journal: arXiv preprint arXiv:2312.10234 year: '2023' url: http://arxiv.org/abs/2312.10234