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

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Paul Dickman


MEB Partners

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Erin Gabriel

Affiliated to Research
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Mark Clements

Senior Lecturer
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Anna Johansson

Assistant Professor
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Michael Sachs


National and International Partners

Els Goetghebeur

Sven Ove Samuelsen

Paul Lambert

Current Ph.D. students and Postdocs

Gustav Jonzon

Phd Student
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Nikolaos Skourlis

Affiliated To Research;Affiliated to Research


Causal bounds for outcome-dependent sampling in observational studies

Journal of the American Statistical Association

Gabriel EE, Sachs MC, Sjölander A.

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