Dec 292016

Clinical and Statistical Considerations in Personalized Medicine (Chapman & Hall/CRC Biostatistics Series)

The Future of Clinical Research and Health Care: From Empirical to Precision Medicine
Clinical and Statistical Considerations in Personalized Medicine explores recent advances related to biomarkers and their translation into clinical development. Leading clinicians, biostatisticians, regulators, commercial professionals, and researchers address the opportunities and challenges in successfully applying biomarkers in drug discovery and preclinical and clinical development.

Robust Biomarkers for Drug Development and Disease Treatment
The first four chapters discuss biomarker development from a clinical perspective. Coverage ranges from an introduction to biomarkers to advances in RNAi screens, epigenetics, and rare diseases as targets for personalized medicine approaches. Subsequent chapters examine the statistical considerations in applying a personalized medicine approach, including multiplicity in pharmacogenomics. The last chapter assesses the regulatory issues involved in using biomarkers.

Improve Patient Care and Reduce Costs and Side Effects
Despite the vast amount of literature on biomarkers, there is no comprehensive book that integrates the clinical and statistical components. This book is one of the first to incorporate both the clinical and statistical aspects of biomarkers in the personalized medicine paradigm. Covering a wide spectrum of personalized medicine-related topics, it presents state-of-the-art techniques for advancing the application of biomarkers in drug discovery and development.

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Dec 262016

High-Yield™ Biostatistics (High-Yield Series)

Features: Used Book in Good Condition
By (author): MD, PhD. Anthony N. Glaser

Part of the successful High-Yield™ Series, High-Yield™ Biostatistics, Second Edition explains concepts, provides examples, and covers the complete range of biostatistics material that can be expected to appear on the USMLE Step 1. New to this edition are references to evidence-based medicine, and information updated to reflect changes in the current USMLE examinations.
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Dec 242016

A Concise Guide to Clinical Trials

Features: Used Book in Good Condition
By (author): Allan Hackshaw

Clinical trials have revolutionized the way disease is prevented, detected and treated, and early death avoided, and they continue to be an expanding area of research. They are central to the work of pharmaceutical companies, and there are many academic and public sector organizations that conduct trials on a wide variety of interventions, including drugs, devices, surgical techniques, and changes in behaviour and lifestyle.

A Concise Guide to Clinical Trials provides a comprehensive yet easy-to-read overview of the design, conduct and analysis of trials. It requires no prior knowledge on the subject as the important concepts are introduced throughout. There are chapters that distinguish between the different types of trials, and an introduction to systematic reviews, health-related quality of life and health economic evaluation. The book also covers the ethical and legal requirements in setting up a clinical trial due to an increase in governance responsibilities and regulations.

This practical guidebook is ideal for busy clinicians and other health professionals who do not have enough time to attend courses or search through extensive textbooks. It will help anyone involved in undertaking clinical research, or those reading about trials. The book is aimed at:

  • Those wishing to learn about clinical trials for the first time, or as a quick reference guide, for example as part of a taught course on clinical trials
  • Health professionals who wish to conduct their own trials, or participate in other people’s studies
  • People who work in pharmaceutical companies, grant funding organisations, or regulatory agencies
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Dec 242016

Medical Statistics at a Glance Workbook

Features: Used Book in Good Condition
By (author): Aviva Petrie, Caroline Sabin

This comprehensive workbook contains a variety of self-assessment methods that allow readers to test their statistical knowledge, put it into practice, and apply it in a medical context, while also providing guidance when critically appraising published literature. It is designed to support the best-selling third edition of Medical Statistics at a Glance, to which it is fully cross-referenced, but may be used independently of it.

Ideal for medical students, junior doctors, researchers and anyone working in the biomedical and pharmaceutical disciplines who wants to feel more confident in basic medical statistics, the title includes:

• Over 80 MCQs, each testing knowledge of a single statistical concept or aspect of study interpretation
• 29 structured questions  to explore in greater depth several statistical techniques or principles, including  the choice of appropriate statistical analyses and the interpretation of study findings
• Templates for the appraisal of clinical trials and observational studies, plus full appraisals of two published papers to demonstrate the use of these templates in practice
• Detailed step-by-step analyses of two substantial data sets (also available at to demonstrate the application of statistical procedures to real-life research

Medical Statistics at a Glance Workbook is the ideal resource to test statistical knowledge and improve analytical and interpretational skills.

Additional resources are available at, including:
• Excel datasets to accompany the data analysis section
• Downloadable PDFs of two templates for critical appraisal
• Links to online further reading
• Supplementary MCQs

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Dec 242016

Essentials of Medical Statistics

Features: Blackwell Publishers
By (author): Betty Kirkwood, Jonathan Sterne

Blackwell Publishing is delighted to announce that this book has been 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 presented in a delightful way. There are many books on statistics for doctors but there are few that are excellent and this is certainly one of them. Statistics is not an easy subject to teach or write about. The authors have succeeded in producing a book that is as good as it can get. 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 introductory textbook, it presents statistics with a clarity and logic that demystifies 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 and impact.

Essential Medical Statistics is supported by a web site at This useful online resource provides statistical datasets to download, as well as sample chapters and future updates.

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Dec 202016

Medical Statistics from Scratch: An Introduction for Health Professionals

Features: Wiley-Interscience

Correctly understanding and using medical statistics is a key skill for all medical students and health professionals.

In an informal and friendly style, Medical Statistics from Scratch provides a practical foundation for everyone whose first interest is probably not medical statistics. Keeping the level of mathematics to a minimum, it clearly illustrates statistical concepts and practice with numerous real world examples and cases drawn from current medical literature.

This fully revised and updated third edition includes new material on: 

  • missing data, random allocation and concealment of data
  • intra-class correlation coefficient
  • effect modification and interaction
  • diagnostic testing and the ROC curve
  • standardisation

Medical Statistics from Scratch is an ideal learning partner for all medical students and health professionals needing an accessible introduction, or a friendly refresher, to the fundamentals of medical statistics.

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Dec 192016

Clinical Trials with Missing Data: A Guide for Practitioners (Statistics in Practice)

By (author): Michael O’Kelly, Bohdana Ratitch

This book provides practical guidance for statisticians, clinicians, and researchers involved in clinical trials in the biopharmaceutical industry, medical and public health organisations. Academics and students needing an introduction to handling missing data will also find this book invaluable.

The authors describe how missing data can affect the outcome and credibility of a clinical trial, show by examples how a clinical team can work to prevent missing data, and present the reader with approaches to address missing data effectively.

The book is illustrated throughout with realistic case studies and worked examples, and presents clear and concise guidelines to enable good planning for missing data. The authors show how to handle missing data in a way that is transparent and easy to understand for clinicians, regulators and patients. New developments are presented to improve the choice and implementation of primary and sensitivity analyses for missing data. Many SAS code examples are included – the reader is given a toolbox for implementing analyses under a variety of assumptions.

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Dec 162016

Statistical Methods for Healthcare Performance Monitoring (Chapman & Hall/CRC Biostatistics Series)

By (author): Alex Bottle, Paul Aylin

Healthcare is important to everyone, yet large variations in its quality have been well documented both between and within many countries. With demand and expenditure rising, it’s more crucial than ever to know how well the healthcare system and all its components – from staff member to regional network – are performing. This requires data, which inevitably differ in form and quality. It also requires statistical methods, the output of which needs to be presented so that it can be understood by whoever needs it to make decisions.

Statistical Methods for Healthcare Performance Monitoring covers measuring quality, types of data, risk adjustment, defining good and bad performance, statistical monitoring, presenting the results to different audiences and evaluating the monitoring system itself. Using examples from around the world, it brings all the issues and perspectives together in a largely non-technical way for clinicians, managers and methodologists.

Statistical Methods for Healthcare Performance Monitoring is aimed at statisticians and researchers who need to know how to measure and compare performance, health service regulators, health service managers with responsibilities for monitoring performance, and quality improvement scientists, including those involved in clinical audits.

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Dec 162016

Statistical Testing Strategies in the Health Sciences (Chapman & Hall/CRC Biostatistics Series)

By (author): Albert Vexler, Alan D. Hutson, Xiwei Chen

Statistical Testing Strategies in the Health Sciences provides a compendium of statistical approaches for decision making, ranging from graphical methods and classical procedures through computationally intensive bootstrap strategies to advanced empirical likelihood techniques. It bridges the gap between theoretical statistical methods and practical procedures applied to the planning and analysis of health-related experiments.

The book is organized primarily based on the type of questions to be answered by inference procedures or according to the general type of mathematical derivation. It establishes the theoretical framework for each method, with a substantial amount of chapter notes included for additional reference. It then focuses on the practical application for each concept, providing real-world examples that can be easily implemented using corresponding statistical software code in R and SAS. The book also explains the basic elements and methods for constructing correct and powerful statistical decision-making processes to be adapted for complex statistical applications.

With techniques spanning robust statistical methods to more computationally intensive approaches, this book shows how to apply correct and efficient testing mechanisms to various problems encountered in medical and epidemiological studies, including clinical trials. Theoretical statisticians, medical researchers, and other practitioners in epidemiology and clinical research will appreciate the book’s novel theoretical and applied results. The book is also suitable for graduate students in biostatistics, epidemiology, health-related sciences, and areas pertaining to formal decision-making mechanisms.

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Dec 062016

Big Data Analytics in Genomics

This contributed volume explores the emerging intersection between big data analytics and genomics. Recent sequencing technologies have enabled high-throughput sequencing data generation for genomics resulting in several international projects which have led to massive genomic data accumulation at an unprecedented pace.  To reveal novel genomic insights from this data within a reasonable time frame, traditional data analysis methods may not be sufficient or scalable, forcing the need for big data analytics to be developed for genomics. The computational methods addressed in the book are intended to tackle crucial biological questions using big data, and are appropriate for either newcomers or veterans in the field.
This volume offers thirteen peer-reviewed contributions, written by international leading experts from different regions, representing Argentina, Brazil, China, France, Germany, Hong Kong, India, Japan, Spain, and the USA.  In particular, the book surveys three main areas: statistical analytics, computational analytics, and cancer genome analytics. Sample topics covered include: statistical methods for integrative analysis of genomic data, computation methods for protein function prediction, and perspectives on machine learning techniques in big data mining of cancer. Self-contained and suitable for graduate students, this book is also designed for bioinformaticians, computational biologists, and researchers in communities ranging from genomics, big data, molecular genetics, data mining, biostatistics, biomedical science, cancer research, medical research, and biology to machine learning and computer science.  Readers will find this volume to be an essential read for appreciating the role of big data in genomics, making this an invaluable resource for stimulating further research on the topic.
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