Conferences  >  Medicine & Healthcare  >  Clinical Data Management, e-Health  >  United Kingdom

Isaac Newton Institute for Mathematical Sciences, Cambridge

This workshop explores challenging applications of causal inference methodology in biomedical research. These include a variety of topics including; clinical trials with the question of suitable causal estimands in view of intercurrent events, the application of causal discovery in epidemiology, advances in quantitative bias analyses and methods of Mendelian randomisation with time-varying exposures. The time-dependent nature of real-world biomedical data, with its special sources of potential bias, requires tailored statistical methods and will be a core aspect of the workshop. The aim is to move beyond the common simple settings of binary point treatments towards methods allowing for realistically complex causal questions taking the practical limitations of typical biomedical data into account. The workshop will highlight cutting-edge developments and foster discussion on future directions in this arguably most important field of application of causal inference.

Probability and Statistics, Game Theory,    Applied Mathematics (in general)