Functions for identification and transportation of causal effects. Provides a conditional causal effect identification algorithm (IDC) by Shpitser, I. and Pearl, J. (2006) http://ftp.cs.ucla.edu/pub/stat_ser/r329-uai.pdf, an algorithm for transportability from multiple domains with limited experiments by Bareinboim, E. and Pearl, J. (2014) http://ftp.cs.ucla.edu/pub/stat_ser/r443.pdf and a selection bias recovery algorithm by Bareinboim, E. and Tian, J. (2015) http://ftp.cs.ucla.edu/pub/stat_ser/r445.pdf. All of the previously mentioned algorithms are based on a causal effect identification algorithm by Tian , J. (2002) http://ftp.cs.ucla.edu/pub/stat_ser/r309.pdf.
For details, see the package vignettes at CRAN and the paper Identifying Causal Effects with the R Package causaleffect
You can install the latest release version from CRAN:
install.packages("causaleffect")
Alternatively, you can install the latest development version by using the devtools package:
install.packages("devtools")
devtools::install_github("santikka/causaleffect")
- Replaced deprecated igraph edge indexing to avoid future warnings.
- Fixed a rare issue when using pruning.
- Fixed an incorrect graph definition in the IDC algorithm.
- The package no longer depends on the 'ggm' package.
- The package no longer requires the 'XML' package, now suggests instead.
- Fixed inconsistency with function arguments when computing causal effects with surrogate experiments using 'aux.effect'.
- Fixed a rare issue with simplification.