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Approximate reciprocal relationship between two cause-specific hazard ratios in COVID-19 data with mutually exclusive events

Author

Listed:
  • Li Wentian

    (The Robert S. Boas Center for Genomics and Human Genetics, The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA)

  • Cetin Sirin

    (Department of Biostatistics, Faculty of Medicine, Amasya University, Amasya, Türkiye)

  • Ulgen Ayse

    (Department of Biostatistics, Faculty of Medicine, Girne American University, Karmi, Cyprus)

  • Cetin Meryem

    (Department of Microbiology, Faculty of Medicine, Amasya University, Amasya, Türkiye)

  • Sivgin Hakan

    (Department of Internal Medicine, Faculty of Medicine, Tokat GaziosmanPasa University, Tokat, Türkiye)

  • Yang Yaning

    (Department of Statistics and Finance, University of Science and Technology of China, Hefei, China)

Abstract

COVID-19 survival data presents a special situation where not only the time-to-event period is short, but also the two events or outcome types, death and release from hospital, are mutually exclusive, leading to two cause-specific hazard ratios (csHR d and csHR r ). The eventual mortality/release outcome is also analyzed by logistic regression to obtain odds-ratio (OR). We have the following three empirical observations: (1) The magnitude of OR is an upper limit of the csHR d : |log(OR)| ≥ |log(csHR d )|. This relationship between OR and HR might be understood from the definition of the two quantities; (2) csHR d and csHR r point in opposite directions: log(csHR d ) ⋅ log(csHR r )

Suggested Citation

  • Li Wentian & Cetin Sirin & Ulgen Ayse & Cetin Meryem & Sivgin Hakan & Yang Yaning, 2024. "Approximate reciprocal relationship between two cause-specific hazard ratios in COVID-19 data with mutually exclusive events," The International Journal of Biostatistics, De Gruyter, vol. 20(1), pages 43-56.
    • Handle: RePEc:bpj:ijbist:v:20:y:2024:i:1:p:43-56:n:1011
    DOI: 10.1515/ijb-2022-0083
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