What can Statistics Contribute to a Causal Understanding?

By O. Aalen, Arnoldo Frigessi. 2007

47 citations recorded by the source corpus.

Subfields: History and Philosophy of Science, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/5e6415f9e2a778271e75215ad10ce14a6170415f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In History and Philosophy of Science

1. Roland R. Ramsahai
2. Stijn Vansteelandt

In Molecular Biology

1. Roland R. Ramsahai
2. T. Martinussen

Citations in the corpus

• Can we believe the DAGs? A comment on the relationship between causal DAGs and mechanisms (2014, background): “More broadly, there is a concept of local dependence 3–5 that has been recently much discussed and that seems a possible tool for formulating stochastic mechanisms.”
• Effective connectivity: Influence, causality and biophysical modeling (2011, unknown): “Further generalizations : We want to end this subsection by mentioning that there is a wealth of theory and numerics for other stochastic (point) processes (Aalen and Frigessi, 2007; Commenges and Gégout-Petit, 2009) that have not yet been, to our knowledge, treated formally in Neuroimaging.”
• Estimation of direct effects for survival data by using the Aalen additive hazards model (2011, background): “The ultimate interest in most aetiological studies is not only to uncover whether an exposure has a causal influence on a particular outcome, but also to understand the mechanisms driving the causal processes that influence the outcome (Aalen and Frigessi, 2007; Commenges and Gégout-Petit, 2009; Van”
• Causal Bounds and Observable Constraints for Non-deterministic Models (2012, background): “For certain applications though, for example, mutations that cause cancer (Aalen and Frigessi, 2007), subject matter knowledge suggests that assumptions about the existence of deterministic mechanisms are unrealistic and spawns controversy (Dawid, 2000).”
• Causality, mediation and time: a dynamic viewpoint (2012, background): “Keywords: Causal inference; Dynamic path analysis; Granger causality; Local independence; Mediation”