MolPAGE Training Workshop on Causal Inference - 19-21 May 2008
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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
Genetics Regression Genetics Regression • 857 views
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