Medical Statistics at a Glance

Published Reviews of the 2nd Edition ''...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, vol.5, issue 1 Published Reviews of the 2nd Edition ''...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, vol.5, issue 1" Published Reviews of the 2nd Edition ''...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, vol.5, issue 1

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 ix Part 1 Handling data 1 1 Types of data 2 2 Data entry 4 3 Error checking and outliers 6 4 Displaying data diagrammatically 8 5 Describing data: the average 10 6 Describing data: the spread 12 7 Theoretical distributions: the Normal distribution 14 8 Theoretical distributions: other distributions 16 9 Transformations 18 Part 2 Sampling and estimation 21 10 Sampling and sampling distributions 22 11 Confidence intervals 24 Part 3 Study design 27 12 Study design I 28 13 Study design II 31 14 Clinical trials 34 15 Cohort studies 37 16 Casecontrol studies 40 Part 4 Hypothesis testing 43 17 Hypothesis testing 44 18 Errors in hypothesis testing 47 Part 5 Basic techniques for analysing data 51 Numerical data 19 Numerical data: a single group 52 20 Numerical data: two related groups 54 21 Numerical data: two unrelated groups 57 22 Numerical data: more than two groups 60 Categorical data 23 Categorical data: a single proportion 63 24 Categorical data: two proportions 66 25 Categorical data: more than two categories 69 Regression and correlation 26 Correlation 72 27 The theory of linear regression 75 28 Performing a linear regression analysis 77 29 Multiple linear regression 81 30 Binary outcomes and logistic regression 85 31 Rates and Poisson regression 89 32 Generalized linear models 93 33 Explanatory variables in statistical models 96 Important considerations 34 Bias and confounding 100 35 Checking assumptions 104 36 Sample size calculations 107 37 Presenting results 111 Part 6 Additional chapters 115 38 Diagnostic tools 116 39 Assessing agreement 119 40 Evidence-based medicine 124 41 Methods for clustered data 127 42 Regression methods for clustered data 130 43 Systematic reviews and meta-analysis 134 44 Survival analysis 138 45 Bayesian methods 142 46 Developing prognostic scores 144 Appendices 147 A Statistical tables 148 B Altmans nomogram for sample size calculations (Chapter 36) 155 C Typical computer output 156 D Checklists and trial profile from the EQUATOR network and critical appraisal templates 169 E Glossary of terms 178 F Chapter numbers with relevant multiple-choice questions and structured questions from Medical Statistics at a Glance Workbook 188 Index 190