Essential Medical Statistics is a classic amongst medical statisticians. An introductory textbook, it presents statistics with a clarity and logic that will demystify the subject, while providing a comprehensive coverage of advanced as well as basic methods.
The second edition of Essential Medical Statistics has been comprehensively revised and updated to include modern statistical methods and modern approaches to statistical analysis, while retaining the approachable and non-mathematical style of the first edition. The book now includes full coverage of the most commonly used regression models, multiple linear regression, logistic regression, Poisson regression and Cox regression, as well as a chapter on general issues in regression modelling. In addition, new chapters introduce more advanced topics such as meta-analysis, likelihood, bootstrapping and robust standard errors, and analysis of clustered data.
Aimed at students of medical statistics, medical researchers, public
health practitioners and practising clinicians using statistics
in their daily work, the book is designed as both a teaching and
a reference text. The format of the book is clear with highlighted
formulae and worked examples, so that all concepts are presented
in a simple, practical and easy-to-understand way. The second edition
enhances the emphasis on choice of appropriate methods with new
chapters on strategies for analysis and measures of association