Causal inference on distribution functions

Causal inference in studies and medical articles

This article has no abstract.

Causal inference based on counterfactuals

BACKGROUND The counterfactual or potential outcome model has become increasingly standard for causal inference in epidemiological and medical studies. DISCUSSION This paper provides an overview on the counterfactual and related approaches. A variety of conceptual as well as practical issues when estimating causal effects are reviewed. These include causal interactions, imperfect experiments, ...

Causal Inference on Event Sequences

Given two event sequences, i.e. two discrete valued time series, of length n can we tell whether they are causally related? Œat is, can we tell whether xn causes yn , whether yn causes xn? Can we do so without having to make assumptions on the distribution of these time series, or about the lag of the causal e‚ect? And, importantly for practical application, can we do so accurately and ecientl...

A Tutorial On Causal Inference

Special issue on causal inference.

We provide a brief editorial introduction to a special issue of The International Journal of Biostatistics dedicated to several papers presented at a workshop held at the Banff International Research Station, Canada, in May 2009.