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Statistics in Clinical Practice
  1. T Seemungal
  1. Barts and The London Medical School, London, UK; tseemungal{at}aol.com

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This is a very clearly written introduction to statistics, suitable for medical students and doctors who need a quick update in order to understand the current literature. Professor Coggon moves rapidly through types of data (continuous, ordinal or univariate and multivariate) to methods of summarising data on which a fair amount of time is spent. Tabular and graphical (dot, line, bar and pie chart) presentations are discussed with numerous illustrations from everyday clinical practice. The interpretation of graphical data and its limitations—a very important part of understanding current medical research—are thoroughly discussed. The concept of probability is introduced and combining probabilities is explained. Sensitivity and specificity are defined here but could more appropriately be placed later as they are, in fact, properties of statistical tests. Hypothesis testing, confidence intervals, and the basis of sample size calculations (though not how to calculate the size of a sample) are also discussed. The author explains the two most common methods of statistical modelling—linear regression and survival analysis—and concludes with a section on meta-analyses and the importance of involving statisticians very early in the planning stage of a study.

This is an excellent introduction to practising statistics in medicine and will be extremely useful for medical students and clinicians alike. Medical researchers will, however, need to follow this text with a more advanced one.

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