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")- 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.
- Fixed a bug with simplification.
- Added a new parameter 'stop_on_nonid' to all identifiability algorithms. Value 'TRUE' mimics old functionality, where an error is produced when a non-identifiable effect is discovered. Value 'FALSE' continues the recursion.
- Fixed a bug in the recoverability algorithm.
- Fixed a bug in the transportability algorithm.
- Fixed a bug related to identification using surrogate outcomes.
- Added a new function 'surrogate.outcome' to compute causal effects using surrogate outcomes.
- Fixed an issue with simplification introduced in version 1.3.6.