Applied Bayesian Statistical Studies in Biology and Medicine

This volume presents the results of biological and medical research with the statistical methods used to obtain them. Nowadays the fields of biology and experimental medicine rely on techniques for the processing of experimental data and for the evaluation of hypotheses. Thus it is increasingly necessary to stimulate awareness of the importance, variety and flexibility of statistical techniques (and of the possible traps that they can hide) by using real data in concrete situations drawn from research activity, instead of hypothetical examples. The approaches taken to deal with the various topics in the book may seem disparate, and the heterogeneity is quite apparent. Nevertheless, although the authors talk about marine biology, physical anthropology, social medicine, population genetics, et cetera, many of the procedures can be traced back to the same fundamental and very common techniques, for example diagnosis and classification, clinical trials, Monte Carlo methods. The book opens with a critical discussion of the relationships between statisticians and researchers written by Professor D.V. Lindley. This volume can serve as a guide for young biologists and physicians who wish to become familiar with the most modern tools of statistical inference, for example - non-parametric discriminant analysis, hierarchical models and related computational techniques.

Table of Contents:
1. Some reflections on the current state of statistics.- 2. Answering two biological questions with a latent class model via MCMC applied to capture-recapture data.- 3. On the Bayesian inference of the Hardy-Weinberg equilibrium model.- 4. Identifying a Bayesian Network for the problem “Hospital and families: the analysis of patient satisfaction with their stay in hospital”.- 5. Reliability of GIST diagnosis based on partial information.- 6. Comparing two groups or treatments-a Bayesian approach.- 7. Two experimental settings in clinical trials: predictive criteria for choosing the sample size in interval estimation.- 8. Attributing a paleoanthropological specimen to a prehistoric population: a Bayesian approach with multivariate B-spline functions.- 9. An example of the subjectivist statistical method for learning from data: Why do whales strand when they do?.- 10. Development and communication of Bayesan methodology for medical device clinical trials.- 11. An adaptive SIR algorithm for Bayesian multilevel inference on categorical data.- 12. Age at death diagnosis by cranial suture obliteration: a Bayesian approach.- 13. Bayesian estimation of restriction fragment length from electrophoretic analysis.

Review :
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)