Biostatistics

Biostatistical methods and techniques

Statistical modeling in twin studies and other studies 

• Analysis of twin data 

• Generalized linear mixed models

• AI neural network models

Analysis of time dependent data

• Longitudinal data analysis

• Recurrent events data

• Time to event models

• Survival analysis of twin data  

Analysis of high-dimensional data

• Non- og semi-parametric methods 

• Regularized models 

• Dimension reduction

• Supervised learning 

• Bootstrap methods

Functional data analysis

• Functional linear models 

• Reproducing Kernel Hilbert spaces

• Stochastic processes

Direct impact and causation

Causal analysis

Collaboration and knowledge sharing

The biostatistical team of researchers at EBB collaborate with several national and international partners. 

• NorTwinCan : Nordic Twin Study of Cancer

• DTR : Danish Twin Research Center

• AgeCare : Academy of Geriatric Cancer Research

• Twin Study at University of Helsinki

• L'Instituto Superiore di Sanitá
  National Institute of Health, Italy

• Danish Society of Theoretical Statistics : DSTS

• Center for Individualized Medicine in Arterial Diseases : CIMA

• Børne- og Ungdomspsykiatri Odense

• NeIC Tryggve : Collaboration for Sensitive Data

• eMindYourHeart : Internet-based treatment of depression and anxiety in patients with ischemic heart disease

• Section of Biostatistics, University of Copenhagen

Teaching and supervision

• Biostatistics I & II

• Advanced Biostatistics (Bootcamp)

• Analysis of Twin Data in Health Sciences

• Artificial Intelligence Learners in Health Science

• Survival Analysis

• Biostatistical Consultancy Service

Editorial board

• Scandinavian Journal of Statistics : Theory and Applications

  Professor Jacob Hjemborg; Danish editor and member of the board