Contains all you need to know to understand statistics in medicine.
Medical Statistics Made Easy has been a perennial bestseller since the first edition was published (it is consistently a #1 bestseller in medical statistics on Amazon).
It is recommended worldwide on a variety of courses and programmes, from undergraduate medicine, through to professional medical qualifications.
It is a book of key statistics principles for anyone studying or working in medicine and healthcare who needs a basic overview of the subject. It is ideal for non-statisticians who need to understand how statistics are used and applied in medicine and medical research.
Using a consistent format, the authors describe the most common statistical methods in turn and then rate them on how difficult they are to understand and how common they are. The worked examples that demonstrate the statistical method in action have been updated to include current articles from the medical literature and now feature a wider range of medical journals.
This fourth edition continues with the same structure as the previous editions, with new sections on cut-off points and ROC curves, as well as a new chapter on choosing the right statistical test. It also features a completely revised and updated 'Statistics at work' section.
Statistics which describe data: Percentages; Mean; Median; Mode; Standard deviation
Statistics which test confidence: Confidence intervals; P values
Statistics which test differences: t tests and other parametric tests; Mann-Whitney and other non-parametric tests; Chi-squared
Statistics which compare risk: Risk ratio; Odds ratio; Risk reduction and numbers needed to treat
Statistics which analyze relationships: Correlation; Regression
Statistics which analyze survival: Survival analysis: life tables and Kaplan-Meier plots; The Cox regression model
Statistics which analyze clinical investigations and screening: Sensitivity, specificity and predictive value; Level of agreement
Statistics at work: Means, standard deviations, medians and odds ratios; Confidence intervals and number needed to treat; Correlation and regression; Survival analysis; Sensitivity, specificity and predictive values; Choosing the right statistical test