Package: causaloptim 0.9.8

causaloptim: An Interface to Specify Causal Graphs and Compute Bounds on Causal Effects

When causal quantities are not identifiable from the observed data, it still may be possible to bound these quantities using the observed data. We outline a class of problems for which the derivation of tight bounds is always a linear programming problem and can therefore, at least theoretically, be solved using a symbolic linear optimizer. We extend and generalize the approach of Balke and Pearl (1994) <doi:10.1016/B978-1-55860-332-5.50011-0> and we provide a user friendly graphical interface for setting up such problems via directed acyclic graphs (DAG), which only allow for problems within this class to be depicted. The user can then define linear constraints to further refine their assumptions to meet their specific problem, and then specify a causal query using a text interface. The program converts this user defined DAG, query, and constraints, and returns tight bounds. The bounds can be converted to R functions to evaluate them for specific datasets, and to latex code for publication. The methods and proofs of tightness and validity of the bounds are described in a paper by Sachs, Jonzon, Gabriel, and Sjölander (2022) <doi:10.1080/10618600.2022.2071905>.

Authors:Michael C Sachs [aut, cre], Erin E Gabriel [aut], Arvid Sjölander [aut], Gustav Jonzon [aut], Alexander A Balke [ctb]

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causaloptim.pdf |causaloptim.html
causaloptim/json (API)
NEWS

# Install 'causaloptim' in R:
install.packages('causaloptim', repos = c('https://sachsmc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/sachsmc/causaloptim/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

20 exports 15 stars 6.33 score 37 dependencies 24 scripts 418 downloads

Last updated 12 months agofrom:f93803cc3c. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 02 2024
R-4.5-win-x86_64OKOct 02 2024
R-4.5-linux-x86_64OKOct 02 2024
R-4.4-win-x86_64OKOct 02 2024
R-4.4-mac-x86_64OKOct 02 2024
R-4.4-mac-aarch64OKOct 02 2024
R-4.3-win-x86_64OKOct 02 2024
R-4.3-mac-x86_64OKOct 02 2024
R-4.3-mac-aarch64OKOct 02 2024

Exports:analyze_graphcausalproblemcheckconstraintscheckcreate_effect_vectorcreate_q_matrixcreate_R_matrixcreate_response_functionget_default_effectgraphrescheckinterpret_boundslatex_boundsoptimize_effectoptimize_effect_2parse_constraintsparse_effectplot_graphresquerychecksimulate_boundsspecify_graphupdate_effect

Dependencies:base64encbslibcachemclicommonmarkcpp11crayondigestfastmapfontawesomefsgluehtmltoolshttpuvigraphjquerylibjsonlitelaterlatticelifecyclemagrittrMatrixmemoisemimepkgconfigpromisesR6rappdirsrcddRcpprlangsassshinysourcetoolsvctrswithrxtable

Code from examples in manuscript

Rendered fromexample-code.Rmdusingknitr::rmarkdownon Oct 02 2024.

Last update: 2022-06-30
Started: 2020-03-09

How to use the causaloptim Shiny app to analyze graphs

Rendered fromshinyapp.Rmdusingknitr::rmarkdownon Oct 02 2024.

Last update: 2023-10-05
Started: 2019-08-15

Improving the speed of computing causal bounds

Rendered fromvertexenum-speed.Rmdusingknitr::rmarkdownon Oct 02 2024.

Last update: 2023-01-21
Started: 2021-01-20