dagitty
Graphical analysis of structural causal models / graphical causal models.
Science Score: 36.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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✓DOI references
Found 4 DOI reference(s) in README -
○Academic publication links
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✓Committers with academic emails
1 of 9 committers (11.1%) from academic institutions -
○Institutional organization owner
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○Scientific vocabulary similarity
Low similarity (11.7%) to scientific vocabulary
Repository
Graphical analysis of structural causal models / graphical causal models.
Basic Info
Statistics
- Stars: 316
- Watchers: 14
- Forks: 52
- Open Issues: 45
- Releases: 2
Metadata Files
README.md
dagitty
This is a collection of algorithms, a GUI frontend and an R package for analyzing graphical causal models (DAGs).
The main components of the repository are:
- jslib: a JavaScript library implementing many DAG algorithms. This library underpins both the web interface and the R package, but could also be used independently, like in node.js.
- gui: HTML interface for a GUI that exposes most of the functions in the JavaScript library.
- r: R package that exposes most of the functions in the JavaScript library.
- website: The current content of dagitty.net, including a version of the GUI (which may be older than the one in gui.
- doc: LaTeX source of the dagitty PDF documentation.
Running the web interface locally
Clone the repository and open the file gui/dags.html in your web browser.
Currently most functionality should work locally, but you will need an internet
connection if you want to load or save DAG models on dagitty.net.
Running the R package
The R package can be installed from CRAN, but this version is not updated very frequently. If you want to install the most recent version of the dagitty R package, you can:
install.packages("remotes") # unless you have it already
remotes::install_github("jtextor/dagitty/r")
If you encounter any problems installing the R package, it is probably not due to dagitty itself, but due to the package "V8" that it depends on. I may try to remove this dependency in a future version.
More information
You can get more information on dagitty at dagitty.net and dagitty.net/learn. The R package is documented through the standard R help interface. There are also a few papers available:
Textor, J., van der Zander, B., Gilthorpe, M. S., Liśkiewicz, M., & Ellison, G. T. H. (2017). Robust causal inference using directed acyclic graphs: the R package ‘dagitty.’ In International Journal of Epidemiology (p. dyw341). Oxford University Press (OUP). https://doi.org/10.1093/ije/dyw341
Ankan, A., Wortel, I. M. N., & Textor, J. (2021). Testing Graphical Causal Models Using the R Package “dagitty.” In Current Protocols (Vol. 1, Issue 2). Wiley. https://doi.org/10.1002/cpz1.45
Owner
- Name: Johannes Textor
- Login: jtextor
- Kind: user
- Location: Nijmegen, The Netherlands
- Company: Radboud University
- Website: johannes-textor.name
- Repositories: 10
- Profile: https://github.com/jtextor
Computational biologist, interested in modelling, Bayesian networks and causality.
GitHub Events
Total
- Issues event: 9
- Watch event: 27
- Issue comment event: 19
- Push event: 1
- Pull request event: 3
- Fork event: 7
Last Year
- Issues event: 9
- Watch event: 27
- Issue comment event: 19
- Push event: 1
- Pull request event: 3
- Fork event: 7
Committers
Last synced: over 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Johannes Textor | j****r@g****e | 82 |
| Johannes Textor | j****r@s****l | 55 |
| Benito van der Zander | b****o@b****e | 38 |
| Johannes Textor | j****r@r****l | 10 |
| Ankur Ankan | a****n@g****m | 10 |
| Benito van der Zander | b****o@b****e | 7 |
| NickCH-K | 4****K | 5 |
| Duncan Murdoch | m****n@g****m | 3 |
| Malcolm Barrett | m****t | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 10 months ago
All Time
- Total issues: 80
- Total pull requests: 26
- Average time to close issues: 7 months
- Average time to close pull requests: 3 months
- Total issue authors: 52
- Total pull request authors: 11
- Average comments per issue: 1.59
- Average comments per pull request: 1.04
- Merged pull requests: 21
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 9
- Pull requests: 1
- Average time to close issues: 12 days
- Average time to close pull requests: 9 days
- Issue authors: 8
- Pull request authors: 1
- Average comments per issue: 1.11
- Average comments per pull request: 1.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- jtextor (14)
- benibela (4)
- behrman (4)
- HeikoBreitsohl (3)
- ghost (2)
- malcolmbarrett (2)
- ohadle (2)
- juandavidgutier (2)
- ThomasSoeiro (2)
- gsverhoeven (2)
- krassowski (2)
- AndrewC19 (1)
- flxflks (1)
- amandacpac (1)
- SimonDedman (1)
Pull Request Authors
- benibela (11)
- malcolmbarrett (5)
- ankurankan (3)
- krassowski (2)
- GustavoGarciaPereira (1)
- jttoivon (1)
- seannyD (1)
- MarkHanly (1)
- jeroen (1)
- NickCH-K (1)
- dmurdoch (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- cran 6,470 last-month
- Total docker downloads: 23,281
- Total dependent packages: 12
- Total dependent repositories: 30
- Total versions: 6
- Total maintainers: 1
cran.r-project.org: dagitty
Graphical Analysis of Structural Causal Models
- Homepage: https://www.dagitty.net
- Documentation: http://cran.r-project.org/web/packages/dagitty/dagitty.pdf
- License: GPL-2
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Latest release: 0.3-4
published over 2 years ago
Rankings
Maintainers (1)
Dependencies
- R >= 3.0.0 depends
- MASS * imports
- V8 * imports
- boot * imports
- grDevices * imports
- graphics * imports
- jsonlite * imports
- methods * imports
- stats * imports
- utils * imports
- base64enc >= 0.1 suggests
- igraph * suggests
- knitr * suggests
- lavaan * suggests
- markdown * suggests
- rmarkdown * suggests
- testthat * suggests
- commander 7.2.0
- globalyzer 0.1.0
- globrex 0.1.2
- node-watch 0.7.3
- qunit 2.18.0
- tiny-glob 0.2.9
- underscore 1.13.2
- qunit ^2.18.0
- underscore ^1.13.2