Medical Statistics from Scratch: An Introduction for Health Professionals

Correctly understanding and using medical statistics is a key skill for all medical students and health professionals. In an informal and friendly style, Medical Statistics from Scratch provides a practical foundation for everyone whose first interest is probably not medical statistics. Keeping the level of mathematics to a minimum, it clearly illustrates statistical concepts and practice with numerous real world examples and cases drawn from current medical literature. This fully revised and updated third edition includes new material on:  missing data, random allocation and concealment of data intra–class correlation coefficient effect modification and interaction diagnostic testing and the ROC curve standardisation Medical Statistics from Scratch is an ideal learning partner for all medical students and health professionals needing an accessible introduction, or a friendly refresher, to the fundamentals of medical statistics.

Preface to the First Edition Preface to the Second Edition Preface to the Third Edition Introduction PART I SOME FUNDAMENTAL STUFF Chapter 1. First things first – the nature of data PART II DESCRIPTIVE STATISTICS Chapter 2. Describing data with tables Chapter 3. Describing data with charts Chapter 4. Describing data from its shape Chapter 5. Describing data with measures of location Chapter 6. Describing data with measures of spread PART III GETTING THE DATA Chapter 7. Confounding – like poor(nearly) always with us Chapter 8. Research Design Part I Observational. Chapter 9. Research Design Part II Experimental studies Chapter 10. Getting the participants for your study.  Ways of sampling Chapter 11. Chance would be a fine thing – the idea of probability Chapter 12. Risk and odds Part V THE INFORMED GUESS – AN INTRODUCTION TO CONFIDENCE INTERVALS Chapter 13. Estimating the value of a single population parameter – the idea of confidence intervals Chapter 14. Using confidence intervals to compare two population parameters Chapter 15. Confidence intervals for the ratio of two population parameters Part VI PUTTING IT TO TEST Chapter 16. Testing hypotheses about the difference between two population parameters Chapter 17. The chi–squared  (χ 2 ) test – what, why, and how? Chapter 18. Testing hypotheses about the ratio of two population parameters Part VII BECOMING ACQUAINTED Chapter 19. Measuring the association between two variables Chapter 20. Measuring agreement VIII GETTING INTO A RELATIONSHIP Chapter 21. Straight line models: linear regression Chapter 22. Curvy models: logistic regression IX FOUR MORE CHAPTERS Chapter 23. Measuring survival Chapter 24. Systematic review and meta–analysis Chapter 25. Diagnostic testing Appendix: Random Number Table References Solutions to Exercises Index