Dan Mayer is Professor of Emergency Medicine, Albany Medical College, New York, USA.

'This is the best book on evidence-based medicine and the foundations for the evidence that I have ever come across. It is very easy to read, and each chapter can be read as a standalone explanation of a particular concept. I highly recommend this for the personal libraries of students, residents and attending physicians.' Doody's Book Reviews

• Preface; Acknowledgements; 1. A brief history of medicine and statistics; 2. What is evidence-based medicine?; 3. Causation; 4. The medical literature: an overview; 5. Searching the medical literature Sandi Pirozzo and Elizabeth Irish; 6. Study design and strength of evidence; 7. Instruments and measurements: precision and validity; 8. Sources of bias; 9. Review of basic statistics; 10. Hypothesis testing; 11. Type I errors and number needed to treat; 12. Negative studies and Type II errors; 13. Risk assessment; 14. Multivariate analysis; 15. Randomized clinical trials (RCTs); 16. Scientific integrity and the responsible conduct of research John E. Kaplan; 17. Applicability and strength of evidence; 18. Communicating evidence to patients Laura J. Zakowski, Shobhina G. Chheda and Christing S. Seibert; 19. Critical appraisal of qualitative research studies Steven R. Simon; 20. An overview of decision making in medicine; 21. Sources of error in the clinical encounter; 22. The use of diagnostic tests; 23. Utility and characteristics of diagnostic tests: likelihood ratios, sensitivity and specificity; 24. Bayes' theorem, predictive values, post-test probabilities, and interval likelihood ratios; 25. Comparing tests and using ROC curves; 26. Incremental gain and the threshold approach to diagnostic testing; 27. Sources of bias and critical appraisal of studies of diagnostic tests; 28. Screening tests; 29. Practice guidelines and clinical prediction rules; 30. Decision analysis and quantifying patient values; 31. Cost-effectiveness analysis; 32. Outcome analysis; 33. Meta-analysis and systematic reviews; Appendix 1. Levels of evidence and grades of recommendations; Appendix 2. Overview of critical appraisal; Appendix 3. Formulas; Appendix 4. Commonly used statistical tests; Appendix 5. Proof of Bayes' theorem; Appendix 6. Using balance sheets to calculate thresholds; Glossary; Bibliography; Index.

Dan Mayer is Professor of Emergency Medicine, Albany Medical College, New York, USA.

'This is the best book on evidence-based medicine and the foundations for the evidence that I have ever come across. It is very easy to read, and each chapter can be read as a standalone explanation of a particular concept. I highly recommend this for the personal libraries of students, residents and attending physicians.' Doody's Book Reviews

• Preface; Acknowledgements; 1. A brief history of medicine and statistics; 2. What is evidence-based medicine?; 3. Causation; 4. The medical literature: an overview; 5. Searching the medical literature Sandi Pirozzo and Elizabeth Irish; 6. Study design and strength of evidence; 7. Instruments and measurements: precision and validity; 8. Sources of bias; 9. Review of basic statistics; 10. Hypothesis testing; 11. Type I errors and number needed to treat; 12. Negative studies and Type II errors; 13. Risk assessment; 14. Multivariate analysis; 15. Randomized clinical trials (RCTs); 16. Scientific integrity and the responsible conduct of research John E. Kaplan; 17. Applicability and strength of evidence; 18. Communicating evidence to patients Laura J. Zakowski, Shobhina G. Chheda and Christing S. Seibert; 19. Critical appraisal of qualitative research studies Steven R. Simon; 20. An overview of decision making in medicine; 21. Sources of error in the clinical encounter; 22. The use of diagnostic tests; 23. Utility and characteristics of diagnostic tests: likelihood ratios, sensitivity and specificity; 24. Bayes' theorem, predictive values, post-test probabilities, and interval likelihood ratios; 25. Comparing tests and using ROC curves; 26. Incremental gain and the threshold approach to diagnostic testing; 27. Sources of bias and critical appraisal of studies of diagnostic tests; 28. Screening tests; 29. Practice guidelines and clinical prediction rules; 30. Decision analysis and quantifying patient values; 31. Cost-effectiveness analysis; 32. Outcome analysis; 33. Meta-analysis and systematic reviews; Appendix 1. Levels of evidence and grades of recommendations; Appendix 2. Overview of critical appraisal; Appendix 3. Formulas; Appendix 4. Commonly used statistical tests; Appendix 5. Proof of Bayes' theorem; Appendix 6. Using balance sheets to calculate thresholds; Glossary; Bibliography; Index.

Dan Mayer is Professor of Emergency Medicine, Albany Medical College, New York, USA.

'This is the best book on evidence-based medicine and the foundations for the evidence that I have ever come across. It is very easy to read, and each chapter can be read as a standalone explanation of a particular concept. I highly recommend this for the personal libraries of students, residents and attending physicians.' Doody's Book Reviews

• Preface; Acknowledgements; 1. A brief history of medicine and statistics; 2. What is evidence-based medicine?; 3. Causation; 4. The medical literature: an overview; 5. Searching the medical literature Sandi Pirozzo and Elizabeth Irish; 6. Study design and strength of evidence; 7. Instruments and measurements: precision and validity; 8. Sources of bias; 9. Review of basic statistics; 10. Hypothesis testing; 11. Type I errors and number needed to treat; 12. Negative studies and Type II errors; 13. Risk assessment; 14. Multivariate analysis; 15. Randomized clinical trials (RCTs); 16. Scientific integrity and the responsible conduct of research John E. Kaplan; 17. Applicability and strength of evidence; 18. Communicating evidence to patients Laura J. Zakowski, Shobhina G. Chheda and Christing S. Seibert; 19. Critical appraisal of qualitative research studies Steven R. Simon; 20. An overview of decision making in medicine; 21. Sources of error in the clinical encounter; 22. The use of diagnostic tests; 23. Utility and characteristics of diagnostic tests: likelihood ratios, sensitivity and specificity; 24. Bayes' theorem, predictive values, post-test probabilities, and interval likelihood ratios; 25. Comparing tests and using ROC curves; 26. Incremental gain and the threshold approach to diagnostic testing; 27. Sources of bias and critical appraisal of studies of diagnostic tests; 28. Screening tests; 29. Practice guidelines and clinical prediction rules; 30. Decision analysis and quantifying patient values; 31. Cost-effectiveness analysis; 32. Outcome analysis; 33. Meta-analysis and systematic reviews; Appendix 1. Levels of evidence and grades of recommendations; Appendix 2. Overview of critical appraisal; Appendix 3. Formulas; Appendix 4. Commonly used statistical tests; Appendix 5. Proof of Bayes' theorem; Appendix 6. Using balance sheets to calculate thresholds; Glossary; Bibliography; Index.