Applied Bayesian Statistical Studies in Biology and Medicine

1. Front Matter

   Pages i-xvii

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2. Some Reflections on the Current State of Statistics

   • D. V. Lindley

   Pages 1-6

3. Answering Two Biological Questions with a Latent Class Model via MCMC Applied to Capture-Recapture Data

   • F. Bartolucci, A. Mira, L. Scaccia

   Pages 7-23

4. On the Bayesian Inference of the Hardy-Weinberg Equilibrium Model

   • F. Bertolino, A. Ratto

   Pages 25-40

5. Identifying a Bayesian Network for the Problem “Hospital and Families: The Analysis of Patient Satisfaction with Their Stay in Hospital”

   • A. Brogini, M. Bolzan, D. Slanzi

   Pages 41-72

6. Reliability of GIST Diagnosis Based on Partial Information

   • A. Capotorti, S. F. Leite

   Pages 73-88

7. Comparing Two Groups or Treatments—A Bayesian Approach

   • J. Deely

   Pages 89-107

8. Two Experimental Settings in Clinical Trials: Predictive Criteria for Choosing the Sample Size in Interval Estimation

   • F. De Santis, M. Perone Pacifico

   Pages 109-130

9. Attributing a Paleoanthropological Specimen to a Prehistoric Population: A Bayesian Approach with Multivariate B-Spline Functions

   • P. Frederic, G. D’Amore, E. Pacciani

   Pages 131-152

10. An Example of the Subjectivist Statistical Method for Learning from Data: Why do Whales Strand when They do?

    • Frank Lad

    Pages 153-187

11. Development and Communication of Bayesan Methodology for Medical Device Clinical Trials

    • A. James O’Malley

    Pages 189-220

12. An Adaptive SIR Algorithm for Bayesian Multilevel Inference on Categorical Data

    • S. Pezzulli

    Pages 221-237

13. Age at Death Diagnosis by Cranial Suture Obliteration: A Bayesian Approach

    • A. Rinaldi, E. Pacciani, M. Di Bacco

    Pages 239-249

14. Bayesian Estimation of Restriction Fragment Length from Electrophoretic Analysis

    • J. Shoemaker, A. Rinaldi

    Pages 251-258

It was written on another occasion· that "It is apparent that the scientific culture, if one means production of scientific papers, is growing exponentially, and chaotically, in almost every field of investigation". The biomedical sciences sensu lato and mathematical statistics are no exceptions. One might say then, and with good reason, that another collection of bio­ statistical papers would only add to the overflow and cause even more confusion. Nevertheless, this book may be greeted with some interest if we state that most of the papers in it are the result of a collaboration between biologists and statisticians, and partly the product of the Summer School th "Statistical Inference in Human Biology" which reaches its 10 edition in 2003 (information about the School can be obtained at the Web site http://www2. stat. unibo. itleventilSito%20scuolalindex. htm). is common experience - and not only This is rather important. Indeed, it in Italy - that encounters between statisticians and researchers are sporadic and hasty. This is not the place to justify this statement, which may sound too severe, as this preface would become much too long. It is sufficient to point out that very often whoever introduces young biologists and medical doctors to inductive reasoning about "data" either does not have a real interest in the concrete and specific meaning of the data or - if intereste- does not have a solid statistical background. In other words, he is usually a "theoretical" statistician or a biological or medical "technician".

• algorithms
• biology
• development
• hospital
• human biology
• Mathematica
• mathematical statistics
• population
• statistical inference
• statistical methods
• statistics
• Vor- und Frühgeschichte

From the reviews:

"The present book is designed to provide a useful presentation of thirteen detailed, well written papers in applied Bayesian statistical methods used in biological and medical research. … the aim of this book is to present a consistent and self-contained overview on results … . The book is of interest to research workers, teachers and students in applied statistics, medicine, genetics, biology, ethology and physical anthropology." (Cryssoula Ganatsiou, Zentralblatt MATH, Vol. 1094 (20), 2006)

• Dipartimento di Scienze Statische, Università di Bologna, Bologna, Italy

  M. Bacco

• Laboratori di Antropologia, Dipartimento di Bologia Animale e Genetica, Università di Firenze, Florence, Italy

  G. D’Amore

• Polo Universitario Asti Studi Superiori, Italy

  F. Scalfari

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