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Borrowing historical information for non-inferiority trials on Covid-19 vaccines

Author

Listed:
  • De Santis Fulvio
  • Gubbiotti Stefania

    (Dipartimento di Scienze Statistiche, Sapienza University of Rome, Roma, Italy)

Abstract

Non-inferiority vaccine trials compare new candidates to active controls that provide clinically significant protection against a disease. Bayesian statistics allows to exploit pre-experimental information available from previous studies to increase precision and reduce costs. Here, historical knowledge is incorporated into the analysis through a power prior that dynamically regulates the degree of information-borrowing. We examine non-inferiority tests based on credible intervals for the unknown effects-difference between two vaccines on the log odds ratio scale, with an application to new Covid-19 vaccines. We explore the frequentist properties of the method and we address the sample size determination problem.

Suggested Citation

  • De Santis Fulvio & Gubbiotti Stefania, 2023. "Borrowing historical information for non-inferiority trials on Covid-19 vaccines," The International Journal of Biostatistics, De Gruyter, vol. 19(1), pages 177-189, May.
    • Handle: RePEc:bpj:ijbist:v:19:y:2023:i:1:p:177-189:n:8
    DOI: 10.1515/ijb-2021-0120
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