One of the exciting new developments in the field of statistics is a renewal of interest in the causality concept. This has led to several new approaches to defining and studying causality in statistical terms. Causality is based on a notion of the past influencing the present and the future. This has very natural links to the type of stochastic processes considered in this book, and it is therefore appropriate to incorporate material on causality.

We shall start with a discussion of causality concepts seen from a statistical point of view. We then continue with various models where causal thinking is applied, ranging from Granger-Schweder causality to counterfactual causality.


Granger Causality Counting Process Local Dependence Event History Analysis Marginal Structural Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media, LLC 2008

Personalised recommendations