released May 2011
Confounding is an important source of bias in epidemiologic studies. With the introduction of causal diagrams (directed acyclic graphs, DAG) a new approach to conceptualize confounding and new rules to identify the minimal sufficient adjustment set have been established (Greenland, Pearl & Robins, Epidemiology, 1999, 10(1):37-48).
The DAG program is a analysis tool, designed to select minimal sufficient adjustment sets within directed acyclic graphs.
The first version (v0.12) of the DAG program can be used as MS DOS command line program. Using the framework Qt (http://qt.nokia.com) we have developed a GUI that allows analyzing and changing causal diagrams more easier.
If you use DAG program (v0.21), you need the same inputfile as they used in the previos version. To learn more about the DAG program, you should read program documentation.
To visualize causal diagrams we refer to the webtool DAGitty (http://www.dagitty.net) developed by Johannes Textor.
Please note that we continuously improve the DAG program. If you have any problems, would like to report a bug or comment on the DAG program, please send an e-mail to email@example.com.
DAG program is available for free download.
|WINDOWS||Version v0.21 (May 12, 2011)||dag_v021.exe||9194 KB|
|WINDOWS||Qt source v0.21 (.zip)||dag_v021.zip||37 KB|
|WINDOWS||Program documentation||DAG program v0.21 Tutorial.pdf||4738 KB|
|MS DOS||Changelog||Changelog.txt||1 KB|
|WINDOWS||Qt source v0.20 (Nov 11, 2010)||dag_v020.zip||36 KB|
|MS DOS||Version v0.12 (March 31, 2010)||dag.exe||1221 KB|
|MS DOS||Program documentation||DAG v0.12 PDF documentation.pdf||114 KB|
|MS DOS||Example files||example.zip||2 KB|
|MS DOS||How to use DAG program v0.12?||DAG program v0.12 usage.pdf||38 KB|
Deutsches Institut für Ernährungsforschung Potsdam-Rehbrücke
German Institute of Human Nutrition Potsdam-Rehbruecke
14558 Nuthetal, Germany
Many thanks to Andreas Stang (Martin-Luther-University of Halle-Wittenberg, Germany) introducing me to the world of causal diagrams and for his assistant on the first version of the DAG program.
I would like to thank a number of people for helpful discussions that clarified my thinking on causal diagrams and for their comments on DAG program: Johannes Textor, Juliane Hardt, Karina Meidtner, Dagmar Drogan and especially Charles Poole.