This guide to statistics for busy mental health professionals describes and applies concepts without mathematics, and includes examples from standard clinical practice. Fully revised and updated in a new edition and covering observational bias, randomization, clinical trials, the overuse of p-values, understanding effect sizes, meta-analysis.
This guide to statistics for busy mental health professionals describes and applies concepts without mathematics, and includes examples from standard clinical practice. Fully revised and updated in a new edition and covering observational bias, randomization, clinical trials, the overuse of p-values, understanding effect sizes, meta-analysis.
S. Nassir Ghaemi is a Professor of Psychiatry and Pharmacology at Tufts University School of Medicine, Tufts Medical Center and is also a Lecturer in Psychiatry at Harvard Medical School in Boston, Massachusetts. He is an associate editor of Acta Psychiatrica Scandinavica, a Life Distinguished Fellow of the American Psychiatric Association, and an Overseas Fellow of the Royal Society of Medicine (UK).
Inhaltsangabe
1. Why data never speak for themselves 2. Why you cannot believe your eyes 3. Levels of evidence 4. Bias 5. Randomization 6. Clinical trials: improving on clinical experience 7. The p-value: uses and misuses 8. Forget p-values: the importance of effect sizes 9. Understanding placebo 10. Understanding confidence intervals 11. Observational studies 12. The alchemy of meta-analysis 13. Bayesian statistics: why your opinion counts 14. Causation 15. A philosophy of statistics 16. Evidence-based medicine: defense and criticism 17. Social and economic factors: peer review, funding, and the conventional wisdom 18. The new canon of psychopharmacology (STAR*D, STEP-BD, CATIE): how clinical trials are misinterpreted 19. False positive maintenance clinical trials in psychiatry 20. How to analyze a study Appendix. Understanding regression Index.
1. Why data never speak for themselves 2. Why you cannot believe your eyes 3. Levels of evidence 4. Bias 5. Randomization 6. Clinical trials: improving on clinical experience 7. The p-value: uses and misuses 8. Forget p-values: the importance of effect sizes 9. Understanding placebo 10. Understanding confidence intervals 11. Observational studies 12. The alchemy of meta-analysis 13. Bayesian statistics: why your opinion counts 14. Causation 15. A philosophy of statistics 16. Evidence-based medicine: defense and criticism 17. Social and economic factors: peer review, funding, and the conventional wisdom 18. The new canon of psychopharmacology (STAR*D, STEP-BD, CATIE): how clinical trials are misinterpreted 19. False positive maintenance clinical trials in psychiatry 20. How to analyze a study Appendix. Understanding regression Index.
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