Michael Crowther, PhD

Founder and CEO

Michael was for many years an academic biostatistician, rising to Associate Professor of Biostatistics at the University of Leicester, before relocating to Stockholm in 2021 to pursue some new challenges. He is an expert in survival analysis and joint longitudinal-survival models, having made numerous contributions to the fields, and widely respected as a statistical software developer. He has developed and taught many training courses on his research, and is a Fellow of the UK Higher Education Academy.


  • PhD in Medical Statistics, University of Leicester, UK, 2014 with thesis “Development and application of methodology for the parametric analysis of complex survival and joint longitudinal-survival data in biomedical research”

  • MSc Medical Statistics, University of Leicester, UK, 2010 with thesis “Individual patient data meta-analysis of survival data using Poisson regression models”

  • MMath Mathematics and Statistics, University of St Andrews, UK, 2009


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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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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