Dicing with Death: Chance, Risk and HealthIf you think that statistics has nothing to say about what you do or how you could do it better, then you are either wrong or in need of a more interesting job. Stephen Senn explains here how statistics determines many decisions about medical care--from allocating resources for health, to determining which drugs to license, to cause-and-effect in relation to disease. He tackles big themes: clinical trials and the development of medicines, life tables, vaccines and their risks or lack of them, smoking and lung cancer and even the power of prayer. He entertains with puzzles and paradoxes and covers the lives of famous statistical pioneers. By the end of the book the reader will see how reasoning with probability is essential to making rational decisions in medicine, and how and when it can guide us when faced with choices that impact our health and/or life. Stephen Senn has been a Professor of Pharmaceutical and Health Statistics at the University College of London since 1995. In 2001 he won George C. Challis Award of the University of Florida for contributions to biostatistics. Senn's previous two books are Statistical Issues in Drug Development (Wiley, 1997) and Cross-over Trials in Clinical Research (Wiley, 1993). He is the member of seven editorial boards including Statistics in Medicine and Pharmaceutical Statistics. |
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accidents alternative amongst analysis apply Arbuthnot average baseline Bayes theorem Bayesian Bernoulli binomial births Bradford Hill breast implants calculate Cambridge chance Chapter clinical trial Cochrane Cochrane Collaboration cohort coin consider correlation coefficient course Daniel deaths difference disease drug effect epidemic equal evidence example fact famous females Figure Finetti Galton given hazard ratio heads Health immunisation individual infected interest Journal Karl Pearson Kermack Laplace Laplace's law law of succession life-table likelihood London lung cancer males mathematician mathematics mean measles medicine meta-analysis mmHg Neyman null hypothesis observed obtain paper patients physician Poisson distribution population possible prob probability of dying problem R. A. Fisher random randomised ratio regression relevant Royal Statistical Society rubella scientists sequence significance test smoking standard statistician Suppose Table tail theory tion tosses treatment true type I error vaccine variability women