Causal Interpretation and Identification of Conditional
Independence Structures
Seminar 1 on CAUSAL INTERPRETATION OF GRAPHICAL MODELS
September 27 - October 8, 1999
Organizing Committee:
Phil Dawid, University College London
Glenn Shafer, Rutgers University
Overview:
Graphical models have been traditionally seen as ways of describing
and manipulating probabilistic conditional independence. However, they
are often given informal causal interpretations, and there now exist
mathematical ways of making these precise and manipulating them.
This research seminar will aim to extend understanding of these methods,
and to explore the scope of graphical modelling as a tool for causal
inference and analysis. Attention will also focus on the nature of the
relationship between causal interpretations and conditional independence
properties of graphical representations, the two main themes of the
overall program.
During the week, September 27 - October 1, 1999, fairly informal
activities are planned.
During the second week, October 4 - 8, 1999, working discussions
are planned on the following topics:
- Monday, October 4, 1999
Causal Thinking in Data Analysis. How might we put more and better
causal thinking in a second course in statistics?
- Tuesday, October 5, 1999
Observation and Experiment. What are the different strategies for
teasing causal information out of observational studies?
- Wednesday, October 6, 1999
What Use Counterfactuals?
- Thursday, October 7, 1999
Causal Logic. Causal information is sometimes too fragmentary to be
organized as a causal model. What then?
- Friday, October 8, 1999
The Causal Interpretations of Graphical Models. Is there more than
one?
INVITED SPEAKERS
| M. Eerola Rolf Nevanlinna Institute |
J. Robins Harvard School of Public Health |
| M. Forster University of Wisconsin |
D. Rubin Harvard University |
| P. Holland University of California |
R. Scheines Carnegie Mellon University |
| S. Lauritzen Aalborg University |
R. Shachter Stanford University |
| W. Oldford University of Waterloo |
M. Studeny Academy of Science, Czech Republic |
| J. Pearl University of California |
L. Wasserman Carnegie Mellon University |
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