The 5th edition of this popular introduction to statistics for the medical and health sciences has undergone a significant revision, with several new chapters added and examples refreshed throughout the book. Yet it retains its central philosophy to explain medical statistics with as little technical detail as possible, making it accessible to a wide audience. Helpful multi-choice exercises are included at the end of each chapter, with answers provided at the end of the book. Each analysis technique is carefully explained and the mathematics kept to minimum. Written in a style suitable for statisticians and clinicians alike, this edition features many real and original examples, taken from the authors' combined many years' experience of designing and analysing clinical trials and teaching statistics. Students of the health sciences, such as medicine, nursing, dentistry, physiotherapy, occupational therapy, and radiography should find the book useful, with examples relevant to their disciplines. The aim of training courses in medical statistics pertinent to these areas is not to turn the students into medical statisticians but rather to help them interpret the published scientific literature and appreciate how to design studies and analyse data arising from their own projects. However, the reader who is about to design their own study and collect, analyse and report on their own data will benefit from a clearly written book on the subject which provides practical guidance to such issues. The practical guidance provided by this book will be of use to professionals working in and/or managing clinical trials, in academic, public health, government and industry settings, particularly medical statisticians, clinicians, trial co-ordinators. Its practical approach will appeal to applied statisticians and biomedical researchers, in particular those in the biopharmaceutical industry, medical and public health organisations.
Pearson's. correlation. Details of the method • It is used to estimate the strength of linear relationship between two continuous variables • It gives a correlation coefficient – often denoted by 'r' The yi and calculations their means ...
For the keen student who does not want a book for mathematicians, this is an excellent first book on medical statistics." Essential Medical Statistics is a classic amongst medical statisticians.
An Introduction to Medical Statistics
This new edition of Medical Statistics at a Glance: Presents key facts accompanied by clear and informative tables and diagrams Focuses on illustrative examples which show statistics in action, with an emphasis on the interpretation of ...
Short, readable, and useful, this book provides the essential, basic information without becoming bogged down in the
... 134, 135, 138 software, 142–144 survival parameterization, 130 nested case–control approach, 6 network algorithms, 52 Newton–Raphson (NR) algorithm, 154 Neyman–Pearson framework, 316, 317 non-informative, 310, 315, 318, 319, 321, ...
A concise, straightforward introduction to medical statistics, this book covers all the topics which a medical student or research worker is likely to encounter in routine work.
This book deals with statistics in medicine in a simple way. The text is supported by abundant examples from medical data. This book aims to explain and simplify the process of data presentation.
Since the publication of the first edition, there have been tremendous advances in biostatistics and bioinformatics. The new edition tries to cover as many important emerging areas and reflect as much progress as possible.
New in this edition: Measuring survival: Kaplan-Meier survival curves; comparingsurvival in two or more groups.Hazard ratios and the Cox regressionmodel. Systematic review: methods and problems; combining results -meta-analytic methods.