Package: dagitty 0.3-4
dagitty: Graphical Analysis of Structural Causal Models
A port of the web-based software 'DAGitty', available at <https://dagitty.net>, for analyzing structural causal models (also known as directed acyclic graphs or DAGs). This package computes covariate adjustment sets for estimating causal effects, enumerates instrumental variables, derives testable implications (d-separation and vanishing tetrads), generates equivalent models, and includes a simple facility for data simulation.
Authors:
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dagitty/json (API)
NEWS
# Install 'dagitty' in R: |
install.packages('dagitty', repos = c('https://jtextor.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jtextor/dagitty/issues
Last updated 7 months agofrom:8a8fd72a74. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 31 2024 |
R-4.5-win | OK | Oct 31 2024 |
R-4.5-linux | OK | Oct 31 2024 |
R-4.4-win | OK | Oct 31 2024 |
R-4.4-mac | OK | Oct 31 2024 |
R-4.3-win | OK | Oct 31 2024 |
R-4.3-mac | OK | Oct 31 2024 |
Exports:adjacentNodesadjustedNodesadjustedNodes<-adjustmentSetsancestorGraphancestorsas.dagittybackDoorGraphcanonicalizechildrenciTestcompleteDAGconvertcoordinatescoordinates<-dagittydconnecteddescendantsdownloadGraphdseparatededgesequivalenceClassequivalentDAGsexogenousVariablesexposuresexposures<-findCyclegetExamplegraphLayoutgraphTypeimpliedConditionalIndependenciesimpliedCovarianceMatrixinstrumentalVariablesis.dagittyisAcyclicisAdjustmentSetisColliderlatentslatents<-lavaanToGraphlocalTestsmarkovBlanketmeasurementPartmoralizeneighboursorientPDAGoutcomesoutcomes<-parentspathsplotLocalTestResultsrandomDAGsetVariableStatussimulateLogisticsimulateSEMspousesstructuralParttoMAGtopologicalOrderingvanishingTetrads