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A Bayesian Survival Analysis of a Historical Dataset: How Long Do Popes Live?

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  • Julian Stander
  • Luciana Dalla Valle
  • Mario Cortina-Borja

Abstract

University courses in statistical modeling often place great emphasis on methodological theory, illustrating it only briefly by means of limited and repeatedly used standard examples. Unfortunately, this approach often fails to actively engage and motivate students in their learning process. The teaching of statistical topics such as Bayesian survival analysis can be enhanced by focusing on innovative applications. Here, we discuss the visualization and modeling of a dataset of historical events comprising the post-election survival times of popes. Inference, prediction, and model checking are performed in the Bayesian framework, with comparisons being made with the frequentist approach. Further opportunities for similar statistical investigations are outlined. Supplementary materials for this article are available online.

Suggested Citation

  • Julian Stander & Luciana Dalla Valle & Mario Cortina-Borja, 2018. "A Bayesian Survival Analysis of a Historical Dataset: How Long Do Popes Live?," The American Statistician, Taylor & Francis Journals, vol. 72(4), pages 368-375, October.
    • Handle: RePEc:taf:amstat:v:72:y:2018:i:4:p:368-375
    DOI: 10.1080/00031305.2017.1328374
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    Cited by:

    1. Kosztyán, Zsolt T. & Jakab, Róbert & Novák, Gergely & Hegedűs, Csaba, 2020. "Survive IT! Survival analysis of IT project planning approaches," Operations Research Perspectives, Elsevier, vol. 7(C).

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