Scion Publishing Ltd
Paperback - 116pp
M. Harris; G. Taylor
Medical Statistics Made Easy 2nd edition continues to provide the easiest possible explanations of the key statistical techniques used throughout the medical literature.
Featuring a comprehensive updating of the 'Statistics at work' section, this new edition retains a consistent, concise, and user-friendly format. Each technique is graded for ease of use and frequency of appearance in the mainstream medical journals.
Medical Statistics Made Easy 2nd edition is essential reading for anyone looking to understand:
* confidence intervals and probability values
* numbers needed to treat
* t tests and other parametric tests
* survival analysis
If you need to understand the medical literature, then you need to read this book.
"This book helps medical students understand the basic concepts of medical statistics starting in a 'step-by-step approach'. The authors have designed the book assuming that the reader has no prior knowledge. It focuses on the most common statistical concepts that are likely to be faced in medical literature.
All chapters are concise and simple to understand. Each chapter starts with an introduction which consists of how important that particular statistical concept is, using a 'star' system. A 'thumbs-up' system shows how easy the statistical concept is to understand. Both these systems indicate time-efficient learning allowing yourself to focus on areas you find most difficult. Following this, there are worked out examples with exam-tips at the end of some chapters.
The last chapter, 'Statistics at Work', shows how medical statistics is put into practice using worked out examples from renowned journals. This helps in assessing the readers own knowledge and gives them confidence in analysis of statistics of a journal.
In conclusion, we would recommend this book as an introduction into medical statistics before plunging into the deep 'statistical' waters! It gives confidence to the reader in taking up the challenge of understanding statistics and [being] able to apply knowledge in analysing medical literature."
Stefanie Zhao Lin Lip & Louise Murchison, Scottish Medical Journal, June 2010
"If ever there was a book that completely lived up to its title, this is it...Perhaps above everything, it is the chapter layout and design that makes this book stand out head and shoulders above the crowd. At the beginning of each chapter two questions are posed how important is the subject in question and how difficult is it to understand? The first is answered on the basis of how often the subject is mentioned / used in papers published in mainstream medical journals. A star rating is then given from one to five with five stars implying use in the majority of papers published. The second question is answered by means of a thumbs up grading system. The more thumbs, the easier the concept is to understand (maximum of five). This, of course, provides a route into statistics for even the most idle of uneducated individuals! Five stars and five thumbs must surely indicate time-efficient learning! At the end of each chapter exam tips (light bulb icon!) are given I doubt anyone could ask for more!
The whole way in which the authors have written this book is commendable; the chapters are succinct, easy to follow and a pleasure to read...Is it value for money? a definite yes even at twice the price. Of course I never exaggerate but if you breathe, you should own this book!"
Ian Pearce, Urology News, June 2010
Statistics which describe data
Percentages; Mean; Median; Mode; Standard deviation
Statistics which test confidence
Confidence intervals; P values
Statistics which test differences
t tests and other parametric tests; Mann-Whitney and other non-parametric tests; Chi-squared
Statistics which compare risk
Risk ratio; Odds ratio; Risk reduction and numbers needed to treat
Statistics which analyse relationships
Statistics which analyse survival
Survival analysis: life tables and Kaplan-Meier plots; The Cox regression model
Statistics which analyse clinical investigations and screening
Sensitivity, specificity and predictive value; Level of agreement and Kappa
Statistics at work
Standard deviation, relative risk and numbers needed to treat; Odds ratios and confidence intervals; Correlation and regression; Survival analysis; Sensitivity, specificity and predictive values