Medical Statistics at a Glance

Now in its fourth edition, Medical Statistics at a Glance is a concise and accessible introduction to this complex subject. It provides clear instruction on how to apply commonly used statistical procedures in an easy-to-read, comprehensive and relevant volume. This new edition continues to be the ideal introductory manual and reference guide to medical statistics, an invaluable companion for statistics lectures and a very useful revision aid.

This new edition of Medical Statistics at a Glance:

• Offers guidance on the practical application of statistical methods in conducting research and presenting results
• Explains the underlying concepts of medical statistics and presents the key facts without being unduly mathematical
• Contains succinct self-contained chapters, each with one or more examples, many of them new, to illustrate the use of the methodology described in the chapter.
• Now provides templates for critical appraisal, checklists for the reporting of randomized controlled trials and observational studies and references to the EQUATOR guidelines for the presentation of study results for many other types of study
• Includes extensive cross-referencing, flowcharts to aid the choice of appropriate tests, learning objectives for each chapter, a glossary of terms and a glossary of annotated full computer output relevant to the examples in the text
• Provides cross-referencing to the multiple choice and structured questions in the companion Medical Statistics at a Glance Workbook

Medical Statistics at a Glance is a must-have text for undergraduate and post-graduate medical students, medical researchers and biomedical and pharmaceutical professionals.

Aviva Petrie is Honorary Associate Professor, Biostatistics Unit, UCL Eastman Dental Institute, London, UK.

Caroline Sabin is Professor of Medical Statistics and Epidemiology, Department of Primary Care and Population Sciences, Royal Free and University College Medical School, London, UK.

Preface

Learning objectives

Handling data

1 Types of data

2 Data entry

3 Error checking and outliers

4 Displaying data diagrammatically

5 Describing data: the ‘average’

6 Describing data: the ‘spread’

7 Theoretical distributions: the Normal distribution

8 Theoretical distributions: other distributions

9 Transformations

Sampling and estimation

10 Sampling and sampling distributions

11 Confidence intervals

Study design

12 Study design I

13 Study design II

14 Clinical trials

15 Cohort studies

16 Case–control studies

Hypothesis testing

17 Hypothesis testing

18 Errors in hypothesis testing

Basic techniques for analysing data

Numerical data

19 Numerical data: a single group

20 Numerical data: two related groups

21 Numerical data: two unrelated groups

22 Numerical data: more than two groups

Categorical data

23 Categorical data: a single proportion

24 Categorical data: two proportions

25 Categorical data: more than two categories

Regression and correlation

26 Correlation

27 The theory of linear regression

28 Performing a linear regression analysis

29 Multiple linear regression

30 Binary outcomes and logistic regression

31 Rates and Poisson regression

32 Generalized linear models

33 Explanatory variables in statistical models

Important considerations

34 Bias and confounding

35 Checking assumptions

36 Sample size calculations

37 Presenting results

Additional chapters

38 Diagnostic tools

39 Assessing agreement

40 Evidence-based medicine

41 Methods for clustered data

42 Regression methods for clustered data

43 Systematic reviews and meta-analysis

44 Survival analysis

45 Bayesian methods

46 Developing prognostic scores

Appendices

A Statistical tables

B Altman’s nomogram for sample size calculations

C Typical computer output

D EQUATOR network checklists and critical appraisal templates

E Glossary of terms

F Chapter numbers with relevant multiple-choice questions and structured questions from Medical Statistics at a Glance Workbook

Index

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