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For clinicians not well-versed in mathematical techniques, medical statistics can be baffling. Understanding these statistics is crucial for the interpretation of literature and the informed judgement of the use of therapies. From 'Abortion rate' to 'Zygosity determination', this accessible introduction to the terminology of medical statistics clearly describes, illustrates and explains over 1500 terms using non-technical language, and without any mathematical formulae! The majority of terms have been updated and revised for this new edition, and almost 150 new definitions have been added, ensuring readers are up to date with the latest practices. Entries are organised alphabetically, and related topics are clearly cross-referenced throughout, to provide fast, easy navigation. Further reading suggestions supplement most definitions, which allows readers to deepen their understanding of the subject. Enabling clinicians and medical students to grasp the meaning of any statistical terms they encounter when studying medical literature, this guide is a real lifesaver.

Medical statistics

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"This book is aimed at anyone who needs a basic introduction to statistics in the health sciences. It is based on many years' experience teaching first year medical and health science students. Many of the examples are taken from Primary Care in the UK, which is where I worked for many years. Throughout I have tried to emphasise that Medical Statistics is not just a bag of tricks, and there are many synergies between the methods. It is now over forty years since Swinscow's original edition, and each edition reflected changes in the understanding of medical statistics. Perhaps the greatest change has occurred since the previous edition,which appeared twelve years ago.Despite the efforts of medical statisticians, there was a widespread misuse of p-values,the cornerstone of conventional statistical inference. This led some journals to ban p-values altogether. It is my view that used properly the p-value is a useful concept but this book, as in previous editions of this book, concentrates on estimation rather than just hypothesis testing. The book tries to steer the reader away from an excessive devotion to p-values, to instil a proper appreciation of their usefulness and to emphasise estimation over significance testing"--

Medical statistics.

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Medical statistics --- Biometry

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"Focusing on a basic understanding of the methods and analyses in health research, Introduction to Biostatistical Applications in Health Research with Microsoft Office Excel, 2e provides statistical concepts for interpreting results using Excel. The book emphasizes the application of methods and presents the most common methodological procedures in health research, which includes multiple regression, ANOVA, ANCOVA, logistic regression, Cox regression, stratified analysis, life table analysis, and nonparametric parallels. Some updates for this new edition: The flowcharts from the first edition will be expanded to include indicators of the assumptions of each procedure. This will be added to facilitate selection of a statistical approach to analyze a particular set of data. The existing twelve chapters describing statistical principals and statistical methods will be maintained. They have been proven to provide students with a clear and useful approach to the subject in use as a textbook and workbook in a graduate statistics course. An additional chapter will be added to the book that discusses the assumptions of statistical procedures. This chapter will describe each assumption, tell how to determine if the assumption is appropriate for a particular set of data, and provide solutions to situations in which the assumptions are not me by the data set. This chapter will provide students and researchers with the information they need to select an appropriate method of analysis and to apply that method to a set of data. The workbook will include a corresponding chapter that will provide students with practice identifying assumptions, testing for their satisfaction, and applying solutions to violation of assumptions. R will also be included to broaden the appeal and audience for the book"--

Microsoft Excel (Computer file) --- Medical statistics --- Biometry --- Electronic spreadsheets -- Computer programs --- Biometry -- Problems, exercises, etc --- Medical statistics -- Problems, exercises, etc --- Biostatistics -- methods --- Mathematical Computing --- Data Interpretation, Statistical --- Software

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"The book fills a void in the literature and available software, providing a crucial link for students and professionals alike to engage in the analysis of spatial and spatio-temporal health data from a Bayesian perspective using R. The book emphasizes the use of MCMC via Nimble, BRugs, and CARBAyes, but also includes INLA for comparative purposes. In addition, a wide range of packages useful in the analysis of geo-referenced spatial data are employed and code is provided. It will likely become a key reference for researchers and students from biostatistics, epidemiology, public health, and environmental science."--

Mathematical statistics --- Medical statistics --- Medical mapping --- Geospatial data --- Geographic information systems --- Information modeling --- R (Computer program language) --- Bayesian statistical decision theory