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Brian D M Tom
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@brian-d-m-tom-1026
Last seen 10.5 years ago
Hi,
I have been asked by Professor Luisa Bernardinelli to advertise the
below workshop on Causal Inference, which takes place on the 19th to
21st May 2008 in Pavia, Italy.
Regards,
Brian Tom
______________________________________________________________________
______
MolPAGE - Molecular Phenotyping to Accelerate Genomic Epidemiology
Training WorkPackage
?CAUSAL INFERENCE"
Pavia (I), May 19-21, 2008
www.unipv.it/molpage_training/training3
COORDINATORS
Luisa Bernardinelli
Carlo Berzuini
FACULTY
Stijn Vansteelandt
Vanessa Didelez
Arvid Sjolander
______________________________________________________________________
______
PLEASE CIRCULATE
OBJECTIVES:
Recent developments on causal inference within the statistical and
artificial intelligence literature have led to important new insights
on
how
to address problems of confounding and selection bias in a wide
variety of
problem settings. The aim of this Course is to review these
developments
and
to provide state-of-the-art statistical solutions for genetic path
identification, and for dealing with problems of confounding due to
population admixture and of selection bias resulting from
ascertainment
conditions in genetic association studies. The first day of the Course
will
focus on probabilistic graphical models, which have their origins in
genetic
path analysis and which provide a natural general framework for
expressing
and manipulating many important concepts in statistical genetics.
Local
computational algorithms can be described in this way, but also
complex
issues of identification in forensic settings, for example, together
with
genetic mapping and pedigree uncertainty can be handled in this
context, as
can issues of causal inference and identification of regulatory
networks.
This part of the course will introduce the basic ideas and illustrate
how
graphical models can be used in a variety of settings. The second day
of
the
Course will focus on statistical techniques to adjust for measured
confounding. Specifically, we will discuss limitations of ordinary
regression adjustment and focus on successful alternatives, such as
inverse
probability weighting estimators in marginal structural models and
G-estimators. These methods will be applied to detect gene-environment
interactions in family-based association studies and to identify
genetic
pathways. The third day of the Course will focus on the use of
Mendelian
randomization for examining the causal effect of a modifiable exposure
on
disease by making use of measured variation in genes of known
function.
Emphasis will be on the assumptions required for using these methods
and on
state-of-the-art analysis techniques. We will end with an introduction
to
graphical search algorithms for unravelling causal genetic networks.
The
Course will include hands-on computer practical sessions during the
afternoons. It is intended for an audience with some previous
familiarity
with statistics, in particular with linear and logistic regression.
For further information, please do not hesitate to contact:
Alessandra Bianchi
Assistant to Prof. Luisa Bernardinelli Universit? di Pavia
Dip.to Scienze Sanitarie Applicate e Psicocomportamentali
Sezione di Statistica medica ed Epidemiologia via A. Bassi, 21 27100
Pavia
tel 0382 987 541 fax 0382 987 570
e-mail lab.statgen at unipv.it
******************************************************************
--
Brian D M Tom (PhD)
MRC Biostatistics Unit
Institute of Public Health
University Forvie Site
Robinson Way
Cambridge CB2 0SR
United Kingdom
Tel +44 1223 330 382
Fax +44 1223 330 388
e-mail brian.tom at mrc-bsu.cam.ac.uk