Developing a Comprehensive, Integrated Framework for Advanced Statistical Analyses of Observational Studies (16w5091)

Organizers

Michal Abrahamowicz (McGill University)

(London School of Hygiene & Tropical Medicine (UK))

Saskia le Cessie (Leiden University Medical Center)

(McGill University)

(Medical Center - University of Freiburg)

(McMaster University)

Description

The Banff International Research Station will host the "Developing a Comprehensive, Integrated Framework for Advanced Statistical Analyses of Observational Studies" workshop from July 3rd to July 8th, 2016.


We are entering the era of big data, whose collection is increasingly automated. Statistical analysis methods are key to maximizing the potential of such data to gain deeper understanding into complex processes affecting human health, economy or environment and, ultimately, improve lives. Yet, the complexity of such processes and data creates numerous analytical challenges, and these need to be tackled coherently to draw reliable, useful conclusions.

This workshop is unique in bringing together statistical experts from across the world, to identify the nature of the challenges; review the ability of existing methods to address these, and devise strategies to tackle some of the most important problems. To maximize its impact on both research community and the actual analyses of data collected in different fields of science, the workshop’s results will be systematically disseminated, through publications and the website of the recently started STRATOS initiative (http://stratos-initiative.org), a worldwide cooperation of leading researchers in statistics.



The Banff International Research Station for Mathematical Innovation and Discovery (BIRS) is a collaborative Canada-US-Mexico venture that provides an environment for creative interaction as well as the exchange of ideas, knowledge, and methods within the Mathematical Sciences, with related disciplines and with industry. The research station is located at The Banff Centre in Alberta and is supported by Canada's Natural Science and Engineering Research Council (NSERC), the U.S. National Science Foundation (NSF), Alberta's Advanced Education and Technology, and Mexico's Consejo Nacional de Ciencia y Tecnología (CONACYT)..