dosearch (version 1.0.11)
Causal Effect Identification from Multiple Incomplete Data
Sources
Description
Identification of causal effects from arbitrary observational and
experimental probability distributions via do-calculus and standard
probability manipulations using a search-based algorithm by
Tikka, Hyttinen and Karvanen (2021) .
Allows for the presence of mechanisms related to selection bias
(Bareinboim and Tian, 2015) ,
transportability (Bareinboim and Pearl, 2014)
,
missing data (Mohan, Pearl, and Tian, 2013)
) and arbitrary combinations
of these. Also supports identification in the presence of context-specific
independence (CSI) relations through labeled directed acyclic graphs
(LDAG). For details on CSIs see (Corander et al., 2019)
.