## Applied Bayesian Statistical Studies in Biology and MedicineM. di Bacco, G. d'Amore, F. Scalfari 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". |

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### Contents

SOME REFLECTIONS ON THE CURRENT STATE OF STATISTICS | 1 |

ANSWERING TWO BIOLOGICAL QUESTIONS WITH A LATENT CLASS MODEL VIA MCMC APPLIED TO CAPTURERECAPTURE DATA | 7 |

ON THE BAYESIAN INFERENCE OF THE HARDYWEINBERG EQUILIBRIUM MODEL | 25 |

IDENTIFYING A BAYESIAN NETWORK FOR THE PROBLEM HOSPITAL AND FAMILIES THE ANALYSIS OF PATIENT SATISFACTION W... | 41 |

RELIABILITY OF GIST DIAGNOSIS BASED ON PARTIAL INFORMATION | 73 |

COMPARING TWO GROUPS OR TREATMENTSA BAYESIAN APPROACH | 89 |

TWO EXPERIMENTAL SETTINGS IN CLINICAL TRIALS PREDICTIVE CRITERIA FOR CHOOSING THE SAMPLE SIZE IN INTERVAL ESTI... | 109 |

ATTRIBUTING A PALEOANTHROPOLOGICAL SPECIMEN TO A PREHISTORIC POPULATION A BAYESIAN APPROACH WITH MULTIVA... | 131 |

AN EXAMPLE OF THE SUBJECTIVIST STATISTICAL METHOD FOR LEARNING FROM DATA WHY DO WHALES STRAND WHEN THEY ... | 153 |

DEVELOPMENT AND COMMUNICATION OF BAYESAN METHODOLOGY FOR MEDICAL DEVICE CLINICAL TRIALS | 189 |

AN ADAPTIVE SIR ALGORITHM FOR BAYESIAN MULTILEVEL INFERENCE ON CATEGORICAL DATA | 221 |

AGE AT DEATH DIAGNOSIS BY CRANIAL SUTURE OBLITERATION A BAYESIAN APPROACH | 239 |

BAYESIAN ESTIMATION OF RESTRICTION FRAGMENT LENGTH FROM ELECTROPHORETIC ANALYSIS | 251 |

### Other editions - View all

Applied Bayesian Statistical Studies in Biology and Medicine M. di Bacco,G. d'Amore,F. Scalfari Limited preview - 2013 |

Applied Bayesian Statistical Studies in Biology and Medicine M. di Bacco,G. d'Amore,F. Scalfari No preview available - 2011 |

Applied Bayesian Statistical Studies in Biology and Medicine M. di Bacco,G. d'Amore,F. Scalfari No preview available - 2011 |

### Common terms and phrases

age at death algorithm allele amplitude analysis approximation assessment assume B-Kp B-spline Bayes Bayes factor Bayesian approach Bayesian network Bolzan calculations capture-recapture cholesterol clinical trial coherent component compute conditional probability considered context coronary corresponding covariates credibility intervals database defined denote Diabetes diagnosis Dipartimento evaluation example Figure frequentist GIST given groups hospital hospitalisation HPD set hyperparameters hypotheses inbreeding inference interval estimation ISTAT Italy Kuntz latent class model latent classes latent variable length likelihood function lunar marginal likelihood MCMC Mesolithic methods multinomial multinomial distribution multivariate normal notation observed obtained optimal sample outcomes parameters patients population possible posterior density posterior distribution posterior probability predictive distribution prior distribution probability distribution problem procedure proposed random relevant sample size sample size determination Section specific standard statistical statisticians stent structure subjectivist suture Table theorem uncertainty Università values variance vector weights whale stranding