Learn and Apply Directed Acyclic Graphs for Causal Inference R package cia version 1.0.0 Causal Inference Assistance (CIA) for performing causal inference within the structural causal modelling framework. Structure learning is performed using partition Markov chain Monte Carlo (Kuipers & Moffa, 2017) and several additional functions have been added to help with causal inference. Kuipers and Moffa (2017) <doi:10.1080/01621459.2015.1133426>. Software Depends: R (>= 4.4.0) Imports: bnlearn (>= 4.9), igraph, doParallel, parallel, foreach, arrangements, graphics, dplyr, rlang, fastmatch, methods, gRain, patchwork, tidyr Suggests: rmarkdown, knitr, testthat (>= 3.0.0), gtools, gRbase, ggplot2, qgraph, dagitty Mathew Varidel <mathew.varidel@sydney.edu.au> Comprehensive R Archive Network (CRAN) Mathew Varidel [aut, cre, cph] (ORCID: <https://orcid.org/0000-0002-1648-8317>), Victor An [ctb] MIT + file LICENSE (https://CRAN.R-project.org/package=cia/LICENSE) 2024-11-13 application/tgz https://CRAN.R-project.org/package=cia doi:10.32614/CRAN.package.cia