Ricardo Berenguer, MS

Associate Biostatistician

Recently graduated with a M.S. in Epidemiology from Columbia University’s Mailman School of Public Health, New York. Obtained experience in both observational and interventional studies at Columbia University (U.S.A.) and Insitituto de Salud Carlos III (Spain) focusing mainly in Cancer Epidemiology. Joined Red Door Analytics in May 2023 as an Associate Biostatistician.


  • M.S. in Epidemiology, Columbia University Mailman School of Public Health, New York, U.S.A., 2022

  • B.Sc. Mathematics, St. Francis College, New York, U.S.A., 2021

  • B.Sc. Biology, St. Francis College, New York, U.S.A., 2021


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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