The do-calculus revisited
J Pearl - arXiv preprint arXiv:1210.4852, 2012 - arxiv.org
The do-calculus was developed in 1995 to facilitate the identification of causal effects in non-
parametric models. The completeness proofs of [Huang and Valtorta, 2006] and [Shpitser …
parametric models. The completeness proofs of [Huang and Valtorta, 2006] and [Shpitser …
External Validity: From Do-Calculus to Transportability Across Populations
J Pearl, E Bareinboim - Probabilistic and causal inference: The works of …, 2022 - dl.acm.org
The generalizability of empirical findings to new environments, settings or popu lations, often
called “external validity,” is essential in most scientific explorations. This paper treats a …
called “external validity,” is essential in most scientific explorations. This paper treats a …
General transportability–synthesizing observations and experiments from heterogeneous domains
The process of transporting and synthesizing experimental findings from heterogeneous
data collections to construct causal explanations is arguably one of the most central and …
data collections to construct causal explanations is arguably one of the most central and …
Identifying causal effects with the R package causaleffect
S Tikka, J Karvanen - arXiv preprint arXiv:1806.07161, 2018 - arxiv.org
Do-calculus is concerned with estimating the interventional distribution of an action from the
observed joint probability distribution of the variables in a given causal structure. All …
observed joint probability distribution of the variables in a given causal structure. All …
Meta-transportability of causal effects: A formal approach
E Bareinboim, J Pearl - Artificial Intelligence and Statistics, 2013 - proceedings.mlr.press
This paper considers the problem of transferring experimental findings learned from multiple
heterogeneous domains to a different environment, in which only passive observations can …
heterogeneous domains to a different environment, in which only passive observations can …
On multi-cause causal inference with unobserved confounding: Counterexamples, impossibility, and alternatives
A D'Amour - arXiv preprint arXiv:1902.10286, 2019 - arxiv.org
Unobserved confounding is a central barrier to drawing causal inferences from
observational data. Several authors have recently proposed that this barrier can be …
observational data. Several authors have recently proposed that this barrier can be …
On the testable implications of causal models with hidden variables
The validity OF a causal model can be tested ONLY IF the model imposes constraints ON
the probability distribution that governs the generated data. IN the presence OF unmeasured …
the probability distribution that governs the generated data. IN the presence OF unmeasured …
Transportability of causal effects: Completeness results
E Bareinboim, J Pearl - Proceedings of the AAAI Conference on …, 2012 - ojs.aaai.org
The study of transportability aims to identify conditions under which causal information
learned from experiments can be reused in a different environment where only passive …
learned from experiments can be reused in a different environment where only passive …
A potential outcomes calculus for identifying conditional path-specific effects
D Malinsky, I Shpitser… - The 22nd International …, 2019 - proceedings.mlr.press
The do-calculus is a well-known deductive system for deriving connections between
interventional and observed distributions, and has been proven complete for a number of …
interventional and observed distributions, and has been proven complete for a number of …
Causal mediation analysis with multiple mediators
RM Daniel, BL De Stavola, SN Cousens… - …, 2015 - Wiley Online Library
In diverse fields of empirical research—including many in the biological sciences—attempts
are made to decompose the effect of an exposure on an outcome into its effects via a …
are made to decompose the effect of an exposure on an outcome into its effects via a …