SWE-REG: Statistical Methods for Register-based Research

High-quality registers alone are not enough to advance medical science. Statistical methods that allow for the best use of registry data are also needed.

SWE-REG is short for the Swedish network for registry-based research. This is a research network funded by the Swedish Research Council to create an environment for research on the development and evaluation of statistical methods for register-based research.

Our research is in four primary areas:

  1. Extend methods for survival and multi-state models to use rich register data better when modelling complex time-to-event outcomes;
  2. Develop methods for causal inference from register data in the presence of unmeasured confounding;
  3. Adapt machine learning methods to survival outcomes for register data
  4. Develop and apply statistical methods for the analysis of ‘big’ register data

SWE-REG is short for the Swedish network for registry-based research. If you are interested in contributing to our research or believe that our methods may be of use in your application area, please contact us.

Contact person

Erin Gabriel

Researcher

MEB Partners

Mark Clements

Lecturer senior

Michael Sachs

Statistician

National and International Partners

Els Goetghebeur

Sven Ove Samuelsen

Paul Lambert

Current Ph.D. students and Postdocs

Adam Brand

PhD student

Research assistants

Gustav Jonzon

PhD student

Publications

Causal bounds for outcome-dependent sampling in observational studies

Journal of the American Statistical Association

Gabriel EE, Sachs MC, Sjölander A.