Brice Maxime Hugues Ozenne
Associate Professor
Section of Biostatistics
Øster Farimagsgade 5 opg. B
1353 København K
I am a biostatistician doing methodological research, software development (for the R software), statistical consultations, and teaching. I have a shared position between the section of biostatistics at the University of Copenhagen and the Neurobiology Research Unit at Rigshospitalet.
Primary fields of research
I am interested in statistical models for handling repeated measurements which typically arise in medical images, psychological questionnaires, or measurements over time. Part of my research is about developing the Latent Variable Models and mixed model for neuro-imaging data with the corresponding statistical inference framework to handle small sample size and multiple testing.
I am also developing methods for assessing treatment effects in registry data, where one has to account for confounding, right-censoring, and competing risks, and time-varying effects.
Finally, I have two side projects one on the assessment of the benefit-risk of a treatment using Generalized Pairwise Comparisons and another on plannign and analyzing sequential trials in presence of pipeline data.
Teaching
Ph.d. course for students in medical science
- Statistical analysis of repeated measurements and clustered data
- Epidemiological methods in medical research (course leader)
MSc course for students in Statistics and Mathematics-Economics
ID: 144764824
Most downloads
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502
downloads
riskRegression: Predicting the risk of an event using Cox regression models
Research output: Contribution to journal › Journal article › Research › peer-review
Published -
347
downloads
Safety and EEG data quality of concurrent high-density EEG and high-speed fMRI at 3 Tesla
Research output: Contribution to journal › Journal article › Research › peer-review
Published -
297
downloads
Predicting Treatment Outcome in Major Depressive Disorder Using Serotonin 4 Receptor PET Brain Imaging, Functional MRI, Cognitive-, EEG-Based, and Peripheral Biomarkers: A NeuroPharm Open Label Clinical Trial Protocol
Research output: Contribution to journal › Journal article › Research › peer-review
Published