# 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](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](gui): HTML interface for a GUI that exposes most of the functions in the JavaScript library. * [r](r): R package that exposes most of the functions in the JavaScript library. * [website](website): The current content of [dagitty.net](https://dagitty.net), including a version of the GUI (which may be older than the one in [gui](gui). * [doc](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](https://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](https://dagitty.net) and [dagitty.net/learn](https://dagitty.net/learn). The R package is documented through the standard R help interface. There are also a few papers available: 1. 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 2. 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