Medical Statistics at a GlanceNow 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 easytoread, 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.

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Contents
Chapters  2 
Error checking and outliers  6 
Displaying data diagrammatically  8 
the spread  12 
the Normal  14 
Transformations  18 
Confidence intervals  24 
Clinical trials  34 
Important considerations 34 Bias and confounding  100 
Checking assumptions  104 
Sample size calculations  107 
Presenting results  111 
Part 1  115 
Diagnostic tools  116 
Assessing agreement  119 
Evidencebased medicine  124 
Casecontrol studies  40 
Errors in hypothesis testing  47 
two related groups  54 
more than two groups  60 
a single proportion  63 
two proportions  66 
more than two categories  69 
Regression and correlation 26 Correlation  72 
The theory of linear regression  75 
Performing a linear regression analysis  77 
Multiple linear regression  81 
Binary outcomes and logistic regression  85 
Rates and Poisson regression  89 
Generalized linear models  93 
Explanatory variables in statistical models  96 
Methods for clustered data  127 
Regression methods for clustered data  130 
Systematic reviews and metaanalysis  134 
Survival analysis  138 
Bayesian methods  142 
Developing prognostic scores  144 
Appendices  147 
A Statistical tables  148 
B Altmans nomogram for sample size calculations Chapter 36  155 
Typical computer output  156 
Checklists and trial profile from the EQUATOR network and critical appraisal templates  169 
E Glossary of terms  178 
F Chapter numbers with relevant multiplechoice questions and structured questions from Medical Statistics at a Glance Workbook  188 
190  
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Common terms and phrases
able adjust analysis Appendix approach approximately assess associated assumptions Aviva Petrie bias calculate Caroline Sabin Chapter clinical cluster coefficient confidence interval confounding correlation Define dependent Describe disease distribution Edition effect equal error estimate event example expected Explain explanatory variables exposure factors followup frequencies give groups height important included increase indicates individuals interest Interpret likelihood logistic regression mean measure Medical methods multiple Normal distribution null hypothesis observations obtained occur odds outcome Pvalue pairs parameter particular patients perform Petrie and Caroline plot points Poisson population predicted probability proportion random range ratio received reference regression regression analysis regression model relationship relative relevant reporting represents residual response risk sample score selection showing significant similar standard Table test statistic treatment trial true units usually variance variation