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

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 tea...

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Bibliographic Details
Published inThe American statistician Vol. 72; no. 4; pp. 368 - 375
Main Authors Stander, Julian, Dalla Valle, Luciana, Cortina-Borja, Mario
Format Journal Article
LanguageEnglish
Published Alexandria Taylor & Francis 02.10.2018
American Statistical Association
Subjects
Bayesian analysis
BUGS
Censoring
Colleges & universities
Datasets
Elections
Frequentist survival analysis
JAGS
Lexis diagram
Machine learning
Model checking
Pope Francis
Posterior predictive distribution
Regression analysis
Statistical methods
Statistical models
Statistics
Survival
Survival analysis
TEACHER'S CORNER
Weibull residuals
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Summary: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.
ISSN:0003-1305
1537-2731
DOI:10.1080/00031305.2017.1328374