The book aims to provide both comprehensive reviews of the classical methods and an introduction to new developments in medical statistics. The topics range from meta analysis, clinical trial design, causal inference, personalized medicine to machine learning and next generation sequence analysis. 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. Many distinguished scholars, who greatly advanced their research areas in statistical methodology as well as practical applications, also have revised several chapters with relevant updates and written new ones from scratch.The new edition has been divided into four sections, including, Statistical Methods in Medicine and Epidemiology, Statistical Methods in Clinical Trials, Statistical Genetics, and General Methods. To reflect the rise of modern statistical genetics as one of the most fertile research areas since the publication of the first edition, the brand new section on Statistical Genetics includes entirely new chapters reflecting the state of the art in the field.Although tightly related, all the book chapters are self-contained and can be read independently. The book chapters intend to provide a convenient launch pad for readers interested in learning a specific topic, applying the related statistical methods in their scientific research and seeking the newest references for in-depth research.

Blackwell Publishing is delighted to announce that this book hasbeen Highly Commended in the 2004 BMA Medical Book Competition.Here is the judges' summary of this book: "This is a technical book on a technical subject but presentedin a delightful way. There are many books on statistics for doctorsbut there are few that are excellent and this is certainly one ofthem. Statistics is not an easy subject to teach or write about.The authors have succeeded in producing a book that is as good asit can get. For the keen student who does not want a book formathematicians, this is an excellent first book on medicalstatistics." Essential Medical Statistics is a classic amongst medicalstatisticians. An introductory textbook, it presents statisticswith a clarity and logic that demystifies the subject, whileproviding a comprehensive coverage of advanced as well as basicmethods. The second edition of Essential Medical Statistics hasbeen comprehensively revised and updated to include modernstatistical methods and modern approaches to statistical analysis,while retaining the approachable and non-mathematical style of thefirst edition. The book now includes full coverage of the mostcommonly used regression models, multiple linear regression,logistic regression, Poisson regression and Cox regression, as wellas a chapter on general issues in regression modelling. Inaddition, new chapters introduce more advanced topics such asmeta-analysis, likelihood, bootstrapping and robust standarderrors, and analysis of clustered data. Aimed at students of medical statistics, medical researchers,public health practitioners and practising clinicians usingstatistics in their daily work, the book is designed as both ateaching and a reference text. The format of the book is clear withhighlighted formulae and worked examples, so that all concepts arepresented in a simple, practical and easy-to-understand way. Thesecond edition enhances the emphasis on choice of appropriatemethods with new chapters on strategies for analysis and measuresof association and impact. Essential Medical Statistics is supported by a web siteat www.blackwellpublishing.com/essentialmedstats. Thisuseful online resource provides statistical datasets to download,as well as sample chapters and future updates.

The book aims to provide both comprehensive reviews of the classical methods and an introduction to new developments in medical statistics. The topics range from meta analysis, clinical trial design, causal inference, personalized medicine to machine learning and next generation sequence analysis. Very broad topics in medical statistics are addressed. Not only is a rigorous theoretical background emphasized but motivation, applications, examples and computational aspects of the related statistical methods are given adequate weightage. The volume thus provides a convenient starting point for readers who want to be familiar with the most current status of an area of interest.

This volume consists of three parts: Part I comprises 11 chapters on the basic concepts of statistics, Part II consists of 10 chapters on multivariate statistics and Part III contains 12 chapters on design and analysis for medical research. The book is written using basic concepts and commonly used methods of design and analysis in medical statistics, incorporating the operation of statistical package SAS and 100 computer experiments for the important statistical phenomena related to each chapter. All necessary data, including reference answers for the exercises, SAS programs for all computer experiments and part of the examples, and data documents for 12 medical researches are available. The Chinese version of this book has been recommended as a textbook of statistics for postgraduate program by the Office of Education Research, Ministry of Education, People's Republic of China.

This long awaited second edition of this bestseller continues toprovide a comprehensive, user friendly, down-to-earth guide toelementary statistics. The book presents a detailed account ofthe most important procedures for the analysis of data, from thecalculation of simple proportions, to a variety of statisticaltests, and the use of regression models for modeling of clinicaloutcomes. The level of mathematics is kept to a minimum to make thematerial easily accessible to the novice, and a multitude ofillustrative cases are included in every chapter, drawn from thecurrent research literature. The new edition has beencompletely revised and updated and includes new chapters on basicquantitative methods, measuring survival, measurement scales,diagnostic testing, bayesian methods, meta-analysis and systematicreviews. "... After years of trying and failing, this is the only book onstatistics that i have managed to read and understand" - NaveedKirmani, Surgical Registrar, South London Healthcare HHS Trust,UK

APPLIED MEDICAL STATISTICS An up-to-date exploration of foundational concepts in statistics and probability for medical students and researchers Medical journals and researchers are increasingly recognizing the need for improved statistical rigor in medical science. In Applied Medical Statistics, renowned statistician and researcher Dr. Jingmei Jiang delivers a clear, coherent, and accessible introduction to basic statistical concepts, ideal for medical students and medical research practitioners. The book will help readers master foundational concepts in statistical analysis and assist in the development of a critical understanding of the basic rationale of statistical analysis techniques. The distinguished author presents information without assuming the reader has a background in specialized mathematics, statistics, or probability. All of the described methods are illustrated with up-to-date examples based on real-world medical research, supplemented by exercises and case discussions to help solidify the concepts and give readers an opportunity to critically evaluate different research scenarios. Readers will also benefit from the inclusion of: A thorough introduction to basic concepts in statistics, including foundational terms and definitions, location and spread of data distributions, population parameters estimation, and statistical hypothesis tests Explorations of commonly used statistical methods, including t-tests,analysis of variance, and linear regression Discussions of advanced analysis topics, including multiple linear regression and correlation, logistic regression, and survival analysis Substantive exercises and case discussions at the end of each chapter Perfect for postgraduate medical students, clinicians, and medical and biomedical researchers, Applied Medical Statistics will also earn a place on the shelf of any researcher with an interest in biostatistics or applying statistical methods to their own field of research.

Explains the purpose of statistical methods in medical studies & analyzes the statistical techniques used by clinical investigators, with special emphasis on studies published in The New England Journal of Medicine. Clarifies fundamental concepts of statistical design & analysis & facilitates the understanding of research results.