[Statlist] Next talk: Thursday, December 15, 2011 with Johannes Textor, University Utrecht

[Cecilia Rey]

ETH and University of Zurich

Proff. P. Buehlmann -  H.R. Kuensch -
M. Maathuis -  S. van de Geer - M. Wolf


***********************************************************
We are glad to announce the following talk

Thursday, December 15, 2011, 16.15h, HG G 19.1

********************************************************

by Johannes Textor, University Utrecht


Title:
Using Causal Diagrams to Dissect Causal from Biasing Effects

Abstract:
A causal diagram (also called Bayesian network, graphical model,
or DAG) encodes assumptions about causal relationships between a
set of observed and unobserved variabels of interest. Provided that
the encoded assumptions are correct, one can use the causal diagram
to determine whether and how it is possible to estimate a causal effect
of interest from observed (non-experimental) data by means of
covariate adjustment. This is a key methodological issue in empirical
disciplines like epidemiology, psychology, and the social sciences.

Depending on the type of causal effect to be estimated (e.g. total,
direct, or mediated effect), there exist different criteria for deciding
on the validity of adjustment for a given covariate set. Unfortunately,
most of the existing criteria are not complete in the sense that an  
adjustment
may still be valid even if criterion is violated. Moreover, they lead to
exponential time algorithms, which may be prohibitive for even  
moderately
sized diagrams.

We propose a new criterion that unifies several existing criteria, and  
is
both sound and complete. Moreover, we discuss under which  
circumstances it is
possible to efficiently enumerate all minimal covariate set in a causal
diagram that fulfill the criterion. Finally, we shortly describe our
implementation of this method in the open source tool DAGitty
(www.dagitty.net), and outline its relevance in current epidemiological
research.

The abstract is also to be found here:  http://stat.ethz.ch/events/research_seminar
__________________________________________
	[[alternative HTML version deleted]]