This will be the final event of a series of training courses and methodological workshops organized in conjunction with an EC-funded project “Molecular Phenotyping for Accelerating Genomic Epidemiology” (MolPAGE) (http://www-1.unipv.it/molpage_training/index.php). The overall aim was to bring to a statistical and biological audience a picture of the statistical methodology relevant to the project. Past courses have dealt with various specific research themes, such as methods for the analysis of data generated by advanced experimental platforms, in genomics, DNA methylation, transcriptomics, metabonomics and proteomics, and methods for causal inference from observational data.

The principal aim of this final workshop is to assess our current and future abilities to address cause-and-effect questions effectively, on the basis of the observational or quasi-experimental data likely to be available in the field of genetic and genomic epidemiology and medicine.  However contributions need not necessarily be focused on the medical/genomic area.

 Among various themes, this workshop will feature a critical evaluation and comparison of general approaches to causal inference, graphical models, potential outcomes, structural equations, longitudinal analysis,  instrumental variable approaches, mendelian randomization, graphical model based approaches to causal inference, causal inference in dynamic systems, in the analysis of longitudinal survival data, in the analysis of clinical trial data and in genetic epidemiology.