Causal Effect Identification from Multiple Incomplete Data Sources

Identification of causal effects from arbitrary observational and experimental probability distributions via do-calculus and standard probability manipulations using a search-based algorithm. Allows for the presence of mechanisms related to selection bias (Bareinboim, E. and Tian, J. (2015) < http://ftp.cs.ucla.edu/pub/stat_ser/r445.pdf>), transportability (Bareinboim, E. and Pearl, J. (2014) < http://ftp.cs.ucla.edu/pub/stat_ser/r443.pdf>), missing data (Mohan, K. and Pearl, J. and Tian., J. (2013) < http://ftp.cs.ucla.edu/pub/stat_ser/r410.pdf>) and arbitrary combinations of these.


News

Changes from version 1.0.1 to 1.0.2

  • Added an example on how to produce an image from the DOT derivation.
  • Added a warning when the response indicator for a proxy variable is not present in any data source.

Changes from version 1.0.0 to 1.0.1

  • Added a Vignette describing the search procedure.

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("dosearch")

1.0.2 by Santtu Tikka, 4 months ago


Browse source code at https://github.com/cran/dosearch


Authors: Santtu Tikka [aut, cre] , Antti Hyttinen [ctb] , Juha Karvanen [ctb]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports Rcpp

Suggests R.rsp, DOT

Linking to Rcpp

System requirements: C++11


See at CRAN