David Machin - Medical Statistics

The right of Stephen J. Walters, Michael J. Campbell, and David Machin to be identified as the authors of this work has been asserted in accordance with law.

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Library of Congress Cataloging‐in‐Publication Data

Names: Campbell, Michael J., 1950- author. | Walters, Stephen John, author. | Machin, David, 1939– author.

Title: Medical statistics : a textbook for the health sciences / Stephen J. Walters, Michael J. Campbell, David Machin.

Description: Fifth edition. | Hoboken, NJ : Wiley-Blackwell, 2021. | Michael J. Campbell's name appears first in earlier editions. | Includes bibliographical references and index.

Identifiers: LCCN 2020029691 (print) | LCCN 2020029692 (ebook) | ISBN 9781119423645 (paperback) | ISBN 9781119423669 (adobe pdf) | ISBN 9781119423652 (epub)

Subjects: MESH: Biometry–methods | Research Design | Statistics as Topic

Classification: LCC R853.S7 (print) | LCC R853.S7 (ebook) | NLM WA 950 | DDC 610.72/7–dc23

LC record available at https://lccn.loc.gov/2020029691LC ebook record available at https://lccn.loc.gov/2020029692

Cover Design: Wiley

Cover Images: Doctor taking patients blood pressure in examination room, © Hero Images/Getty Images; Cardiogram of heart on paper, © Shevchuk Boris/ Getty Images; Crowded Istiklal street in Istanbul, © Todor Tsvetkov/Getty Images

It is more than 13 years since the last edition of Medical Statistics: A Textbook for the Health Sciences was published and it has proven to be popular. This preface outlines the major changes and updates made since that edition was published.

All the chapters have been revised and updated. With simpler statistical methods it is useful to be able to carry out an analysis for oneself, to help fully understand its usefulness and its limitations. However, with the advent of public domain software for the analysis of data, ever more complex statistical methods are available to the researcher. These advanced methods have been incorporated in many elementary medical statistics syllabuses. A student today needs to understand the application and limitations of these methods to be able to fully evaluate articles in many main stream medical journals. To this end we have introduced new chapters on diagnostic tests, linear modelling, logistic modelling and a further one covering briefly more advanced topics such as random effects modelling and Poisson regression. At all times the emphasis is on understanding why such techniques should be used, their limitations, and how the results of such analyses are to be displayed.

Since the last edition, medical statistics has faced a number of challenges. One of the main ones is the problem of replication. A study is published, with a significant P ‐value, but another study addressing the same research question fails to replicate this result. This can often cause consternation amongst among readers of research. We discuss this issue in Chapter 18on Meta‐analysis. A related issue is the mis‐use of P ‐values. This has been a major discussion point in the research community and we include this in our coverage of P ‐values in Chapter 6.

We have found that quizzes within lectures are a useful method of consolidating a student's understanding of a topic. Each chapter contains a new set of multiple‐choice questions that can be used to test knowledge for the individual reader, or can be used by a lecturer, perhaps with a polling device to see how many students have understood a particular point.

Stephen J. WaltersMichael J. CampbellDavid MachinJuly 2020

1 1.1 Introduction

2 1.2 Why Use Statistics?

3 1.3 Statistics is About Common Sense and Good Design

4 1.4 How a Statistician Can Help

Statistical analysis features in the majority of papers published in health care journals. Most health care practitioners will need a basic understanding of statistical principles, but not necessarily full details of statistical techniques. Medical statisticians should be consulted early in the planning of a study as they can contribute in a variety of ways and not just once all the data have been collected. Thus, medical statistics can influence good research by improving the design of studies as well as suggesting the optimum analysis of the results and their reporting.

Although some health care practitioners may not carry out medical research, they will definitely be consumers of medical research. Thus, it is incumbent on them to be able to discern good studies from bad, to be able to verify whether the conclusions of a study are valid and to understand the limitations of such studies. The current emphasis on evidence‐based medicine (EBM), or more comprehensively evidence‐based health care (EBHC), requires that health care practitioners consider critically all evidence about whether a specific treatment works and this requires basic statistical knowledge.