Caroline Dietrich, PhD

Executive Director of Biostatistics

Caroline Dietrich is a biostatistician with over ten years of experience working in register-based epidemiological research. She joined Red Door Analytics part-time in March 2023 as Principal Biostatistician, before becoming Director of Applied Biostatistics in July 2023, and Executive Director of Biostatistics in August 2024. Caroline’s current role includes responsibility for project oversight across all RDA departments, business development, and of course, hands-on statistical analyses.

Caroline also remains in the Cancer Epidemiology group at the Clinical Epidemiology Division (Department of Medicine Solna, Karolinska Institutet), where she works on clinical research within lymphoma and colorectal cancer, and statistical methods development with a particular focus on survivorship and methods for multi-state modelling.

Education

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Videos

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 […]
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Videos

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 […]
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Statistical Primers

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 […]
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