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DAGs With Omitted Objects Displayed (DAGWOOD) is a framework to help reveal key hidden assumptions in a causal DAG. This package provides an implementation of the DAGWOOD algorithm. Further description can be found in Haber et al (2022) <doi:10.1016/j.annepidem.2022.01.001>.
Version: | 0.1.4 |
Imports: | dagitty |
Suggests: | ggdag |
Published: | 2022-03-22 |
DOI: | 10.32614/CRAN.package.dagwood |
Author: | Noah Haber [aut, cre] |
Maintainer: | Noah Haber <noahhaber at stanford.edu> |
License: | MIT + file LICENSE |
NeedsCompilation: | no |
CRAN checks: | dagwood results |
Reference manual: | dagwood.pdf |
Package source: | dagwood_0.1.4.tar.gz |
Windows binaries: | r-devel: dagwood_0.1.4.zip, r-release: dagwood_0.1.4.zip, r-oldrel: dagwood_0.1.4.zip |
macOS binaries: | r-release (arm64): dagwood_0.1.4.tgz, r-oldrel (arm64): dagwood_0.1.4.tgz, r-release (x86_64): dagwood_0.1.4.tgz, r-oldrel (x86_64): dagwood_0.1.4.tgz |
Old sources: | dagwood archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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