Medical Statistics at a Glance

Medical Statistics at a Glance is a concise and accessible introduction and revision aid for this complex subject. The self-contained chapters explain the underlying concepts of medical statistics and provide a guide to the most commonly used statistical procedures. This new edition of Medical Statistics at a Glance:* Presents key facts accompanied by clear and informative tables and diagrams* Focuses on illustrative examples which show statistics in action, with an emphasis on the interpretation of computer data analysis rather than complex hand calculations* Includes extensive cross-referencing, a comprehensive glossary of terms and flow-charts to make it easier to choose appropriate tests* Now provides the learning objectives for each chapter* Includes a new chapter on Developing Prognostic Scores* Includes new or expanded material on study management, multi-centre studies, sequential trials, bias and different methods to remove confounding in observational studies, multiple comparisons, ROC curves and checking assumptions in a logistic regression analysis* The companion website at www.medstatsaag.com contains supplementary material including an extensive reference list and multiple choice questions (MCQs) with interactive answers for self-assessment. Medical Statistics at a Glance will appeal to all medical students, junior doctors and researchers in biomedical and pharmaceutical disciplines. Reviews of the previous editions "The more familiar I have become with this book, the more I appreciate the clear presentation and unthreatening prose. It is now a valuable companion to my formal statistics course." -International Journal of Epidemiology "I heartily recommend it, especially to first years, but it's equally appropriate for an intercalated BSc or Postgraduate research. If statistics give you headaches - buy it. If statistics are all you think about - buy it." -GKT Gazette "...I unreservedly recommend this book to all medical students, especially those that dislike reading reams of text. This is one book that will not sit on your shelf collecting dust once you have graduated and will also function as a reference book." -4th Year Medical Student, Barts and the London Chronicle, Spring 2003

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"Overall, Medical Statistics at a Glance is very useful to students who are aiming to learn basic medical statistics concepts. Clinicians and statistics students can keep a copy of this book as a quick initial reference. This book is highly recommended as an excellent Medical Statistics guide." (Journal of Biopharmaceutical Statistics, August 2010)

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Aviva Petrie, Head of Biostatistics Unit and Senior Lecturer, Eastman Dental Institute, University College London; Honorary Lecturer in Medical Statistics, Medical Statistics Unit, London School of Hygiene and Tropical Medicine Caroline Sabin, Professor of Medical Statistics and Epidemiology, Department of Primary Care and Population Sciences, Royal Free and University College Medical School, London.

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Preface Learning objectives Handling data 1 Types of data 2 Data entry 3 Error checking and outliers 4 Displaying data graphically 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 67 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 Glossary of terms Index

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