Hannah Bower is a biostatistician with several years experience working with register-based epidemiological data. Previously, Hannah was Director of Applied Biostatistics at Red Door Analytics, where she led the applied team and developed our first on demand training course in survival analysis. Hannah now works at the Department of Medicine Solna, Karolinska Institutet, working with research projects in the inflammatory joint diseases group.
Hannah Bower, PhD
Biostatistician, Karolinska Institutet
State-of-the-art statistical models for modern HTA
At @RedDoorAnalytics, we develop methodology and software for efficient modelling of biomarkers, measured repeatedly over time, jointly with survival outcomes, which are being increasingly used in cancer settings. We have also developed methods and software for general non-Markov multi-state survival analysis, allowing for the development of more plausible natural history models, where patient history can […]Learn more
Multilevel (hierarchical) survival models: Estimation, prediction, interpretation
Hierarchical time-to-event data is common across various research domains. In the medical field, for instance, patients are often nested within hospitals and regions, while in education, students are nested within schools. In these settings, the outcome is typically measured at the individual level, with covariates recorded at any level of the hierarchy. This hierarchical structure […]Learn more
What are competing risks?
Competing risks In survival analysis, competing risks refer to the situation when an individual is at risk of experiencing an event that precludes the event under study to occur. Competing risks commonly occur in studies of cause-specific mortality, as all other causes of death than the one under study might happen before the individuals “have […]Learn more